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  • 1.
    Aaro, Gustav
    Linköpings universitet, Institutionen för datavetenskap.
    Smartphone Based Indoor Positioning Using Wi-Fi Round Trip Time and IMU Sensors2020Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    While GPS long has been an industry standard for localization of an entity or person anywhere in the world, it loses much of its accuracy and value when used indoors. To enable services such as indoor navigation, other methods must be used. A new standard of the Wi-Fi protocol, IEEE 802.11mc (Wi-Fi RTT), enables distance estimation between the transmitter and the receiver based on the Round-Trip Time (RTT) delay of the signal. Using these distance estimations and the known locations of the transmitting Access Points (APs), an estimation of the receiver’s location can be determined. In this thesis, a smartphone Wi-Fi RTT based Indoor Positioning System (IPS) is presented using an Unscented Kalman Filter (UKF). The UKF using only RTT based distance estimations as input, is established as a baseline implementation. Two extensions are then presented to improve the positioning performance; 1) a dead reckoning algorithm using smartphone sensors part of the Inertial Measurement Unit (IMU) as an additional input to the UKF, and 2) a method to detect and adjust distance measurements that have been made in Non-Line-of-Sight (NLoS) conditions. The implemented IPS is evaluated in an office environment in both favorable situations (plenty of Line-of-Sight conditions) and sub-optimal situations (dominant NLoS conditions). Using both extensions, meter level accuracy is achieved in both cases as well as a 90th percentile error of less than 2 meters.

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  • 2. Beställ onlineKöp publikationen >>
    Abbas, Muhammad
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    On the Implementation of Integer and Non-Integer Sampling Rate Conversion2012Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The main focus in this thesis is on the aspects related to the implementation of integer and non-integer sampling rate conversion (SRC). SRC is used in many communication and signal processing applications where two signals or systems having different sampling rates need to be interconnected. There are two basic approaches to deal with this problem. The first is to convert the signal to analog and then re-sample it at the desired rate. In the second approach, digital signal processing techniques are utilized to compute values of the new samples from the existing ones. The former approach is hardly used since the latter one introduces less noise and distortion. However, the implementation complexity for the second approach varies for different types of conversion factors. In this work, the second approach for SRC is considered and its implementation details are explored. The conversion factor in general can be an integer, a ratio of two integers, or an irrational number. The SRC by an irrational numbers is impractical and is generally stated for the completeness. They are usually approximated by some rational factor.

    The performance of decimators and interpolators is mainly determined by the filters, which are there to suppress aliasing effects or removing unwanted images. There are many approaches for the implementation of decimation and interpolation filters, and cascaded integrator comb (CIC) filters are one of them. CIC filters are most commonly used in the case of integer sampling rate conversions and often preferred due to their simplicity, hardware efficiency, and relatively good anti-aliasing (anti-imaging) characteristics for the first (last) stage of a decimation (interpolation). The multiplierless nature, which generally yields to low power consumption, makes CIC filters well suited for performing conversion at higher rate. Since these filters operate at the maximum sampling frequency, therefore, are critical with respect to power consumption. It is therefore necessary to have an accurate and efficient ways and approaches that could be utilized to estimate the power consumption and the important factors that are contributing to it. Switching activity is one such factor. To have a high-level estimate of dynamic power consumption, switching activity equations in CIC filters are derived, which may then be used to have an estimate of the dynamic power consumption. The modeling of leakage power is also included, which is an important parameter to consider since the input sampling rate may differ several orders of magnitude. These power estimates at higher level can then be used as a feed-back while exploring multiple alternatives.

    Sampling rate conversion is a typical example where it is required to determine the values between existing samples. The computation of a value between existing samples can alternatively be regarded as delaying the underlying signal by a fractional sampling period. The fractional-delay filters are used in this context to provide a fractional-delay adjustable to any desired value and are therefore suitable for both integer and non-integer factors. The structure that is used in the efficient implementation of a fractional-delay filter is know as Farrow structure or its modifications. The main advantage of the Farrow structure lies in the fact that it consists of fixed finite-impulse response (FIR) filters and there is only one adjustable fractional-delay parameter, used to evaluate a polynomial with the filter outputs as coefficients. This characteristic of the Farrow structure makes it a very attractive structure for the implementation. In the considered fixed-point implementation of the Farrow structure, closed-form expressions for suitable word lengths are derived based on scaling and round-off noise. Since multipliers share major portion of the total power consumption, a matrix-vector multiple constant multiplication approach is proposed to improve the multiplierless implementation of FIR sub-filters.

    The implementation of the polynomial part of the Farrow structure is investigated by considering the computational complexity of different polynomial evaluation schemes. By considering the number of operations of different types, critical path, pipelining complexity, and latency after pipelining, high-level comparisons are obtained and used to short list the suitable candidates. Most of these evaluation schemes require the explicit computation of higher order power terms. In the parallel evaluation of powers, redundancy in computations is removed by exploiting any possible sharing at word level and also at bit level. As a part of this, since exponents are additive under multiplication, an ILP formulation for the minimum addition sequence problem is proposed.

    Delarbeten
    1. Power Estimation of Recursive and Non-Recursive CIC Filters Implemented in Deep-Submicron Technology
    Öppna denna publikation i ny flik eller fönster >>Power Estimation of Recursive and Non-Recursive CIC Filters Implemented in Deep-Submicron Technology
    2010 (Engelska)Ingår i: Proceedings of International Conference on Green Circuits and Systems (ICGCS), 2010, Date: 21-23 June, 2010, IEEE , 2010, s. 221-225Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    The power modeling of different realizations of cascaded integrator-comb (CIC) decimation filters has been a subject of several recent works. In this work we have extended these with modeling of leakage power, which is an important factor since the input sample rate may differ several orders of magnitude. Furthermore, we have pointed out the importance of the input wordlength on the comparison of recursive and nonrecursive implementations.

    Ort, förlag, år, upplaga, sidor
    IEEE, 2010
    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-70451 (URN)10.1109/ICGCS.2010.5543063 (DOI)978-1-4244-6877-5 (ISBN)978-1-4244-6876-8 (ISBN)
    Konferens
    International Conference on Green Circuits and Systems (ICGCS), June 21–23, Shanghai, China
    Tillgänglig från: 2011-09-20 Skapad: 2011-09-08 Senast uppdaterad: 2015-03-11Bibliografiskt granskad
    2. Switching Activity Estimation of CIC Filter Integrators
    Öppna denna publikation i ny flik eller fönster >>Switching Activity Estimation of CIC Filter Integrators
    2010 (Engelska)Ingår i: Proceedings of Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia), 2010, Date:22-24 Sept. 2010, IEEE , 2010, s. 21-24Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    In this work, a method for estimation of the switching activity in integrators is presented. To achieve low power, it is always necessary to develop accurate and efficient methods to estimate the switching activity. The switching activities are then used to estimate the power consumption. In our work, the switching activity is first estimated for the general purpose integrators and then it is extended for the estimation of switching activity in cascaded integrators in CIC filters.

    Ort, förlag, år, upplaga, sidor
    IEEE, 2010
    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-70452 (URN)10.1109/PRIMEASIA.2010.5604971 (DOI)978-1-4244-6736-5 (ISBN)978-1-4244-6735-8 (ISBN)
    Konferens
    Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia), 22-24 September, Shanghai, China
    Anmärkning
    ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. MUHAMMAD ABBAS and Oscar Gustafsson, Switching Activity Estimation of CIC Filter Integrators, 2010, Asia Pacific Conf. on Postgraduate Research in Microelectronics and Electronics, Shanghai, China. http://dx.doi.org/10.1109/PRIMEASIA.2010.5604971 Tillgänglig från: 2011-09-20 Skapad: 2011-09-08 Senast uppdaterad: 2015-03-11Bibliografiskt granskad
    3. Scaling of fractional delay filters based on the Farrow structure
    Öppna denna publikation i ny flik eller fönster >>Scaling of fractional delay filters based on the Farrow structure
    2009 (Engelska)Ingår i: Proceedings of IEEE International Symposium on Circuits and Systems, 2009. ISCAS 2009, Piscataway: IEEE , 2009, s. 489-492Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    In this work we consider scaling of fractional delay filters using the Farrow structure. Based on the observation that the subfilters approximate the Taylor expansion of a differentiator, we derive estimates of the L2-norm scaling values at the outputs of each subfilter as well as at the inputs of each delay multiplier. The scaling values can then be used to derive suitable wordlengths in a fixed-point implementation.

    Ort, förlag, år, upplaga, sidor
    Piscataway: IEEE, 2009
    Nationell ämneskategori
    Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-51070 (URN)10.1109/ISCAS.2009.5117792 (DOI)000275929800123 ()978-1-4244-3827-3 (ISBN)
    Konferens
    IEEE International Symposium on Circuits and Systems, 24-27 May 2009, Taipei,Taiwan
    Tillgänglig från: 2009-10-15 Skapad: 2009-10-15 Senast uppdaterad: 2018-09-01Bibliografiskt granskad
    4. Computational and Implementation Complexity of Polynomial Evaluation Schemes
    Öppna denna publikation i ny flik eller fönster >>Computational and Implementation Complexity of Polynomial Evaluation Schemes
    2011 (Engelska)Ingår i: Proceedings of NORCHIP, 2011 Date:14-15 Nov. 2011, IEEE conference proceedings, 2011, s. 1-6Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    In this work, we consider the computational complexity of different polynomial evaluation schemes. By considering the number of operations of different types, critical path, pipelining complexity, and latency after pipelining, high-level comparisons are obtained. These can then be used to short list suitable candidates for an implementation given the specifications. Not only multiplications are considered, but they are divided into data-data multiplications, squarers, and data-coefficient multiplications, as the latter can be optimized depending on implementation architecture and application.

    Ort, förlag, år, upplaga, sidor
    IEEE conference proceedings, 2011
    Nyckelord
    Adders, Computer architecture, Delay, Filtering algorithms, ISO, Pipeline processing, Polynomials
    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-73935 (URN)10.1109/NORCHP.2011.6126735 (DOI)978-1-4577-0515-1 (ISBN)978-1-4577-0514-4 (ISBN)
    Konferens
    NORCHIP 2011. The Nordic Microelectronics event, 29th Norchip Conference 14-15 November 2011, Lund, Sweden
    Tillgänglig från: 2012-01-17 Skapad: 2012-01-17 Senast uppdaterad: 2015-03-11Bibliografiskt granskad
    5. Low-Complexity Parallel Evaluation of Powers Exploiting Bit-Level Redundancy
    Öppna denna publikation i ny flik eller fönster >>Low-Complexity Parallel Evaluation of Powers Exploiting Bit-Level Redundancy
    2010 (Engelska)Ingår i: Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2010, 7-10 Nov. 2010 / [ed] Michael B. Matthews, Washington, DC, USA: IEEE Computer Society , 2010, s. 1168-1172Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    In this work, we investigate the problem of computing any requested set of power terms in parallel using summations trees. This problem occurs in applications like polynomial approximation, Farrow filters (polynomial evaluation part) etc. In the proposed technique, the partial product of each power term is initially computed independently. A redundancy check is then made in each and among all partial products matrices at bit level. The redundancy here relates to the fact that same three partial products may be present in more than one columns, and, hence, can be mapped to the same full adder. The proposed algorithm is tested for different sets of powers and wordlengths to exploit the sharing potential.

    Ort, förlag, år, upplaga, sidor
    Washington, DC, USA: IEEE Computer Society, 2010
    Serie
    Asilomar Conference on Signals, Systems and Computers. Conference Record, ISSN 1058-6393
    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-70453 (URN)10.1109/ACSSC.2010.5757714 (DOI)978-1-4244-9722-5 (ISBN)
    Konferens
    Signals, Systems and Computers (ASILOMAR), 2010, 7-10 Nov. 2010 , Pacific Grove, CA, USA
    Tillgänglig från: 2011-09-20 Skapad: 2011-09-08 Senast uppdaterad: 2015-03-11Bibliografiskt granskad
    6. Integer Linear Programming Modeling of Addition Sequences With Additional Constraints for Evaluation of Power Terms
    Öppna denna publikation i ny flik eller fönster >>Integer Linear Programming Modeling of Addition Sequences With Additional Constraints for Evaluation of Power Terms
    (Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    In this work, an integer linear programming (ILP) based model is proposed for the computation of a minimal cost addition sequence for a given set of integers. Since exponents are additive under multiplication, the minimal length addition sequence will provide an optimal solution for the evaluation of a requested set of power terms. This in turn finds application in, e.g., window-based exponentiation for cryptography and polynomial evaluation. Not only is an optimal model proposed, the model is extended to consider different costs for multipliers and squarers as well as controlling the depth of the resulting addition sequence.

    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-73936 (URN)
    Tillgänglig från: 2012-01-17 Skapad: 2012-01-17 Senast uppdaterad: 2015-03-11Bibliografiskt granskad
    7. Switching Activity Estimation of DDFS Phase Accumulators
    Öppna denna publikation i ny flik eller fönster >>Switching Activity Estimation of DDFS Phase Accumulators
    (Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    In this letter, equations for the one’s probability and switching activities for direct digital frequency synthesis (DDFS) phase accumulators are derived. These results are useful for obtaining good accuracy estimated of both leakage and dynamic power consumption for the phase accumulator and the phase-to-magnitude converter.

    Nationell ämneskategori
    Teknik och teknologier
    Identifikatorer
    urn:nbn:se:liu:diva-73937 (URN)
    Tillgänglig från: 2012-01-17 Skapad: 2012-01-17 Senast uppdaterad: 2015-03-11Bibliografiskt granskad
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    On the Implementation of Integer and Non-Integer Sampling Rate Conversion
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    omslag
  • 3.
    Abbas, Muhammad
    et al.
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Oscar
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Johansson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    On the Fixed-Point Implementation of Fractional-Delay Filters Based on the Farrow Structure2013Ingår i: IEEE Transactions on Circuits and Systems Part 1: Regular Papers, ISSN 1549-8328, E-ISSN 1558-0806, Vol. 60, nr 4, s. 926-937Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, the fixed-point implementation of adjustable fractional-delay filters using the Farrow structure is considered. Based on the observation that the sub-filters approximate differentiators, closed-form expressions for the L-2-norm scaling values at the outputs of each sub-filter as well as at the inputs of each delay multiplier are derived. The scaling values can then be used to derive suitable word lengths by also considering the round-off noise analysis and optimization. Different approaches are proposed to derive suitable word lengths including one based on integer linear programming, which always gives an optimal allocation. Finally, a new approach for multiplierless implementation of the sub-filters in the Farrow structure is suggested. This is shown to reduce register complexity and, for most word lengths, require less number of adders and subtracters when compared to existing approaches.

  • 4.
    Abbas, Muhammad
    et al.
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Oscar
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Johansson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Scaling of fractional delay filters based on the Farrow structure2009Ingår i: Proceedings of IEEE International Symposium on Circuits and Systems, 2009. ISCAS 2009, Piscataway: IEEE , 2009, s. 489-492Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this work we consider scaling of fractional delay filters using the Farrow structure. Based on the observation that the subfilters approximate the Taylor expansion of a differentiator, we derive estimates of the L2-norm scaling values at the outputs of each subfilter as well as at the inputs of each delay multiplier. The scaling values can then be used to derive suitable wordlengths in a fixed-point implementation.

  • 5.
    Abd-Elmagid, Mohamed A.
    et al.
    Virginia Tech, VA 24061 USA.
    Dhillon, Harpreet S.
    Virginia Tech, VA 24061 USA.
    Pappas, Nikolaos
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    A Reinforcement Learning Framework for Optimizing Age of Information in RF-Powered Communication Systems2020Ingår i: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 68, nr 8, s. 4747-4760Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we study a real-time monitoring system in which multiple source nodes are responsible for sending update packets to a common destination node in order to maintain the freshness of information at the destination. Since it may not always be feasible to replace or recharge batteries in all source nodes, we consider that the nodes are powered through wireless energy transfer (WET) by the destination. For this system setup, we investigate the optimal online sampling policy (referred to as the age-optimal policy) that jointly optimizes WET and scheduling of update packet transmissions with the objective of minimizing the long-term average weighted sum of Age of Information (AoI) values for different physical processes (observed by the source nodes) at the destination node, referred to as the sum-AoI. To solve this optimization problem, we first model this setup as an average cost Markov decision process (MDP) with finite state and action spaces. Due to the extreme curse of dimensionality in the state space of the formulated MDP, classical reinforcement learning algorithms are no longer applicable to our problem even for reasonable-scale settings. Motivated by this, we propose a deep reinforcement learning (DRL) algorithm that can learn the age-optimal policy in a computationally-efficient manner. We further characterize the structural properties of the age-optimal policy analytically, and demonstrate that it has a threshold-based structure with respect to the AoI values for different processes. We extend our analysis to characterize the structural properties of the policy that maximizes average throughput for our system setup, referred to as the throughput-optimal policy. Afterwards, we analytically demonstrate that the structures of the age-optimal and throughput-optimal policies are different. We also numerically demonstrate these structures as well as the impact of system design parameters on the optimal achievable average weighted sum-AoI.

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  • 6.
    Abualigah, Laith
    et al.
    Al al Bayt Univ, Jordan; Al Ahliyya Amman Univ, Jordan; Lebanese Amer Univ, Lebanon; Middle East Univ, Jordan; Appl Sci Private Univ, Jordan; Univ Sains Malaysia, Malaysia; Sunway Univ Malaysia, Malaysia.
    Oliva, Diego
    Univ Guadalajara, Mexico.
    Jia, Heming
    Sanming Univ, Peoples R China.
    Gul, Faiza
    Air Univ, Pakistan.
    Khodadadi, Nima
    Florida Int Univ, FL USA.
    Hussien, Abdelazim
    Linköpings universitet, Institutionen för datavetenskap, Programvara och system. Linköpings universitet, Tekniska fakulteten. Fayoum Univ, Egypt.
    Al Shinwan, Mohammad
    Appl Sci Private Univ, Jordan.
    Ezugwu, Absalom E.
    North West Univ, South Africa.
    Abuhaija, Belal
    Wenzhou Kean Univ, Peoples R China.
    Abu Zitar, Raed
    Sorbonne Univ Abu Dhabi, U Arab Emirates.
    Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems2023Ingår i: Multimedia tools and applications, ISSN 1380-7501, E-ISSN 1573-7721, Vol. 83, nr 11, s. 32613-32653Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Recently, optimization problems have been revised in many domains, and they need powerful search methods to address them. In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. The proposed method is based on enhancing the search process of the Prairie Dog Optimization Algorithm (PDOA) by using the primary updating mechanism of the Dwarf Mongoose Optimization Algorithm (DMOA). The main aim of the proposed IPDOA is to avoid the main weaknesses of the original methods; these weaknesses are poor convergence ability, the imbalance between the search process, and premature convergence. Experiments are conducted on 23 standard benchmark functions, and the results are compared with similar methods from the literature. The results are recorded in terms of the best, worst, and average fitness function, showing that the proposed method is more vital to deal with various problems than other methods.

  • 7.
    Adam, Wettring
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Adaptive Filtering and Nonlinear Models for Post-processing of Weather Forecasts2015Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Kalman filters have been used by SMHI to improve the quality of their forecasts. Until now they have used a linear underlying model to do this. In this thesis it is investigated whether the performance can be improved by the use of nonlinear models such as polynomials and neural networks. The results suggest that an improvement is hard to achieve by this approach and that it is likely not worth the effort to implement a nonlinear model.

    Ladda ner fulltext (pdf)
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  • 8.
    Afzali, Maryam
    et al.
    University of Leeds, Leeds, United Kingdom; University of Cardiff, United Kingdom.
    Pieciak, Tomasz
    Universidad de Valladolid, Spain.
    Jones, Derek K.
    Cardiff University, United Kingdom.
    Schneider, Jürgen E.
    Leeds University, United Kingdom.
    Özarslan, Evren
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Cumulant expansion with localization: A new representation of the diffusion MRI signal2022Ingår i: Frontiers in Neuroimaging, E-ISSN 2813-1193, Vol. 1Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Diffusion MR is sensitive to the microstructural features of a sample. Fine-scale characteristics can be probed by employing strong diffusion gradients while the low b-value regime is determined by the cumulants of the distribution of particle displacements. A signal representation based on the cumulants, however, suffers from a finite convergence radius and cannot represent the ‘localization regime' characterized by a stretched exponential decay that emerges at large gradient strengths. Here, we propose a new representation for the diffusion MR signal. Our method provides not only a robust estimate of the first three cumulants but also a meaningful extrapolation of the entire signal decay.

    Ladda ner fulltext (pdf)
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  • 9.
    Agheli, Pouya
    et al.
    EURECOM, France.
    Pappas, Nikolaos
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Kountouris, Marios
    EURECOM, France.
    Semantic Source Coding for Two Users with Heterogeneous Goals2022Ingår i: 2022 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM 2022), IEEE , 2022, s. 4983-4988Konferensbidrag (Refereegranskat)
    Abstract [en]

    We study a multiuser system in which an information source provides status updates to two monitors with heterogeneous goals. Semantic filtering is first performed to select the most useful realizations for each monitor. Packets are then encoded and sent so that each monitor can timely fulfill its goal. In this regard, some realizations are important for both monitors, while every other realization is informative for only one monitor. We determine the optimal real codeword lengths assigned to the selected packet arrivals in the sense of maximizing a weighted sum of semantics-aware utility functions for the two monitors. Our analytical and numerical results provide the optimal design parameters for different arrival rates and highlight the improvement in timely status update delivery using semantic filtering and source coding.

  • 10.
    Ahlander, Jesper
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Posluk, Maria
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Deployment Strategies for High Accuracy and Availability Indoor Positioning with 5G2020Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Indoor positioning is desired in many areas for various reasons, such as positioning products in industrial environments, hospital equipment or firefighters inside a building on fire. One even tougher situation where indoor positioning can be useful is locating a specific object on a shelf in a commercial setting.

    This thesis aims to investigate and design different network deployment strategies in an indoor environment in order to achieve both high position estimation accuracy and availability. The investigation considers the two positioning techniques downlink time difference of arrival, DL-TDOA, and round trip time, RTT. Simulations of several deployments are performed in two standard scenarios which mimic an indoor open office and an indoor factory, respectively.

    Factors having an impact on the positioning accuracy and availability are found to be deployment geometry, number of base stations, line-of-sight conditions and interference, with the most important being deployment geometry. Two deployment strategies are designed with the goal of optimising the deployment geometry. In order to achieve both high positioning accuracy and availability in a simple, sparsely cluttered environment, the strategy is to deploy the base stations evenly around the edges of the deployment area. In a more problematic, densely cluttered environment the approach somewhat differs. The proposed strategy is now to identify and strategically place some base stations in the most cluttered areas but still place a majority of the base stations around the edges of the deployment area.

    A robust positioning algorithm is able to handle interference well and to decrease its impact on the positioning accuracy. The cost, in terms of frequency resources, of using more orthogonal signals may not be worth the small improvement in accuracy and availability.

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  • 11.
    Ahlberg, Jesper
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem.
    Blomquist, Esbjörn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem.
    Online Identification of Running Resistance and Available Adhesion of Trains2011Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Två viktiga fysikaliska aspekter som bestämmer prestandan för ett tåg i drift är det totala gångmotståndet som verkar på hela tåget, samt den tillgängliga adhesionen (användbara hjul-räl-friktionen) för framdrivning och bromsning. Från de tillgängliga signalerna önskas identifiering, samt prediktering, av dessa två storheter, under drift. Med målet att förbättra precisionen av dessa skattningar undersöker detta examensarbete potentialen av skattning och prediktering av gångmotstånd och adhesion med hjälp av Extended KalmanFiltering.

    Slutsatsen är att problem med observerbarhet och känslighet uppstår, vilket resulterar i ett behov av sofistikerade metoder att numeriskt beräkna acceleration från en hastighetssignal. Metoden smoothing spline approximation visar sig ge de bästa resultaten för denna numeriska derivering. Känsligheten och dess medförda krav på hög precision, speciellt på accelerationssignalen, resulterar i ett behov av högre samplingsfrekvens. Ett behov av andra adekvata metoder att tillföra ytterligare information, eller att förbättra modellerna, ger upphov till möjliga framtida utredningar inom området.

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    Ahlberg, Blomquist - Online Identification of Running Resistance and Available Adhesion of Trains
  • 12.
    Ahlberg, Jörgen
    Linköpings universitet, Institutionen för systemteknik, Bildkodning. Linköpings universitet, Tekniska högskolan.
    An active model for facial feature tracking2002Ingår i: EURASTP journal an applied signal processing, ISSN 1110-8657, E-ISSN 1687-0433, Vol. 2002, nr 6, s. 566-571Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a system for finding and tracking a face and extract global and local animation parameters from a video sequence. The system uses an initial colour processing step for finding a rough estimate of the position, size, and inplane rotation of the face, followed by a refinement step drived by an active model. The latter step refines the previous estimate, and also extracts local animation parameters. The system is able to track the face and some facial features in near real-time, and can compress the result to a bitstream compliant to MPEG-4 face and body animation.

  • 13.
    Ahlberg, Jörgen
    FOI, SE-58111 Linkoping, Sweden.
    Optimizing Object, Atmosphere, and Sensor Parameters in Thermal Hyperspectral Imagery2017Ingår i: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 55, nr 2, s. 658-670Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We address the problem of estimating atmosphere parameters (temperature and water vapor content) from data captured by an airborne thermal hyperspectral imager and propose a method based on linear and nonlinear optimization. The method is used for the estimation of the parameters (temperature and emissivity) of the observed object as well as sensor gain under certain restrictions. The method is analyzed with respect to sensitivity to noise and the number of spectral bands. Simulations with synthetic signatures are performed to validate the analysis, showing that the estimation can be performed with as few as 10-20 spectral bands at moderate noise levels. The proposed method is also extended to exploit additional knowledge, for example, measurements of atmospheric parameters and sensor noise. Additionally, we show how to extend the method in order to improve spectral calibration.

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  • 14.
    Ahlberg, Jörgen
    et al.
    Division of Information Systems, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Pandzic, Igor
    Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia.
    Facial Action Tracking2011Ingår i: Handbook of Face Recognition / [ed] Stan Z. Li, Anil K. Jain, London: Springer London, 2011, 2, s. 461-486Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    This chapter explains the basics of parametric face models used for face and facial action tracking as well as fundamental strategies and methodologies for tracking. A few tracking algorithms serving as pedagogical examples are described in more detail.

  • 15.
    Ahlström, Christer
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik.
    Liljefeldt, Olle
    Hult, Peter
    Linköpings universitet, Institutionen för medicinsk teknik.
    Ask, Per
    Linköpings universitet, Institutionen för medicinsk teknik.
    Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction.2005Ingår i: Medicinteknikdagarna, 2005, Vol. 12, s. 812-815Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    Heart sounds (HS) obscure the interpretation of lung sounds (LS). This letter presents a new method to detect and remove this undesired disturbance. The HS detection algorithm is based on a recurrence time statistic that is sensitive to changes in a reconstructed state space. Signal segments that are found to contain HS are removed, and the arising missing parts are replaced with predicted LS using a nonlinear prediction scheme. The prediction operates in the reconstructed state space and uses an iterated integrated nearest trajectory algorithm. The HS detection algorithm detects HS with an error rate of 4% false positives and 8% false negatives. The spectral difference between the reconstructed LS signal and an LS signal with removed HS was 0 34 0 25, 0 50 0 33, 0 46 0 35, and 0 94 0 64 dB/Hz in the frequency bands 20–40, 40–70, 70–150, and 150–300 Hz, respectively. The cross-correlation index was found to be 99.7%, indicating excellent similarity between actual LS and predicted LS. Listening tests performed by a skilled physician showed high-quality auditory results.

  • 16.
    Ahlström, Per
    Linköpings universitet, Institutionen för systemteknik. Linköpings universitet, Tekniska högskolan.
    Signalprediktering i vitt gaussiskt brus med hjälp av ett adaptivt signalanpassat filter1976Rapport (Övrigt vetenskapligt)
    Abstract [sv]

    Ett signalanpassat filter har ett impulssvar som är den exiterandesignalens spegelbild . Ett dylikt filter maximerar vid en viss tidpunkt signalbrusförhållandet på utgången.

    Ett adaptivt transversalfilter styrt av en gradientkännande algoritm, vilken maximerar signalbrusförhållandet på filterutgången, har studerats. Det spegelvända impulssvaret har använts som prediktion av signalen. Denna prediktion har, vid simulering gjord på dator, ej visat sig vara bättre än en klassisk prediktion med en ren summering av brusstörda upplagor av signalen. Inte ens då dylika summerade upplagor av den brusstörda signalenanvänts som insignal till filtret har signalprediktionen via filtrets impulssvar uppvisat ett lägre kvadratiskt medelfel än d en klassiska.

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    Signalprediktering i vitt gaussiskt brus med hjälp av ett adaptivt signalanpassat filter
  • 17.
    Ahmad, Shakeel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Elektroniska komponenter. Linköpings universitet, Tekniska högskolan.
    Dabrowski, Jerzy
    Linköpings universitet, Institutionen för systemteknik, Elektroniska komponenter. Linköpings universitet, Tekniska högskolan.
    Cancellation of Spurious Spectral Components in One-Bit Stimuli Generator2010Ingår i: Proceedings of IEEEInternational Conference on Signals and Electronic Systems, (ICSES 10) / [ed] Andrzej Pułka and Tomasz Golonek, IEEE , 2010, s. 393-396Konferensbidrag (Refereegranskat)
    Abstract [en]

    This work presents a cancellation technique of non-linear distortion components of one-bit digital stimulus sequence which is generated in software by a ΣΔ modulator. The stimulus is stored in a cyclic memory and applied to a circuit under test through a driving buffer and a simple lowpass reconstruction filter. The distortion components originate from buffer imperfections which result in a possible asymmetry between rising and falling edges of a NRTZ waveform representing the encoded stimulus. We show that the distortion components can be cancelled by using a simple predistortion technique. In addition an on-chip DC-calibrated ADC can be used to identify the second-order nonlinear products of the driving buffer. This procedure allows for cancellation of all the second-order distortions before the actual test and it can be extended to the third order terms as well.

  • 18.
    Ahmad, Shakeel
    et al.
    Linköpings universitet, Institutionen för systemteknik. Linköpings universitet, Tekniska fakulteten. Univ Management & Technol, Pakistan.
    Dabrowski, Jerzy
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    One-Bit Sigma Delta-Encoded Stimulus Generation for On-Chip ADC Test2020Ingår i: Journal of Circuits, Systems and Computers, ISSN 0218-1266, Vol. 29, nr 15, artikel-id 2050245Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents an application of the Sigma Delta modulation technique to the on-chip dynamic test for analog-to-digital converters (ADCs). The required stimulus such as a single- or two-tone signal is encoded into one-bit Sigma Delta sequence, which is applied to an ADC under test through a driving buffer and a simple low-pass reconstruction filter. By a systematic approach, we select the order and type of a Sigma Delta modulator and develop a frequency plan suitable for the spectral measurement. In this way, we achieve a high dynamic range suitable for spectral harmonic and intermodulation distortion tests for ADCs. For high frequency measurements (up to the Nyquist frequency), we propose a novel low-pass/band-pass modulation scheme that allows to avoid harmful effects of the low-frequency quantization noise. Also we address the distortion components which originate from the buffer imperfections for a nonreturn-to-zero waveform representing the encoded stimulus. We show that the low-frequency distortion components can be cancelled by using a simple iterative predistortion technique supported by measurements with a DC-calibrated ADC. By correlation between low- and high-frequency components also the high frequency distortions can be largely reduced. The presented techniques are illustrated by simulation results of an ADC under test.

  • 19.
    Ahmadi, Shervin Parvini
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Hansson, Anders
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Pakazad, Sina Khoshfetrat
    C3 Ai, CA USA.
    Distributed localization using Levenberg-Marquardt algorithm2021Ingår i: EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, E-ISSN 1687-6180, Vol. 2021, nr 1, artikel-id 74Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we propose a distributed algorithm for sensor network localization based on a maximum likelihood formulation. It relies on the Levenberg-Marquardt algorithm where the computations are distributed among different computational agents using message passing, or equivalently dynamic programming. The resulting algorithm provides a good localization accuracy, and it converges to the same solution as its centralized counterpart. Moreover, it requires fewer iterations and communications between computational agents as compared to first-order methods. The performance of the algorithm is demonstrated with extensive simulations in Julia in which it is shown that our method outperforms distributed methods that are based on approximate maximum likelihood formulations.

  • 20.
    Ahmadian, Amirhossein
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Ding, Yifan
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Eilertsen, Gabriel
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Lindsten, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Unsupervised Novelty Detection in Pretrained Representation Space with Locally Adapted Likelihood Ratio2024Ingår i: International Conference on Artificial Intelligence and Statistics 2024, Proceedings of Machine Learning Research, 2024Konferensbidrag (Refereegranskat)
  • 21.
    Ahmed Aamir, Syed
    et al.
    Linköpings universitet, Institutionen för systemteknik. Linköpings universitet, Tekniska högskolan.
    Harikumar, Prakash
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Wikner, Jacob J
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Frequency compensation of high-speed, low-voltage CMOS multistage amplifiers2013Ingår i: IEEE International Symposium on Circuits and Systems (ISCAS), 2013, IEEE conference proceedings, 2013, s. 381-384Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents the frequency compensation of high-speed, low-voltage multistage amplifiers. Two frequency compensation techniques, the Nested Miller Compensation with Nulling Resistors (NMCNR) and Reversed Nested Indirect Compensation (RNIC), are discussed and employed on two multistage amplifier architectures. A four-stage pseudo-differential amplifier with CMFF and CMFB is designed in a 1.2 V, 65-nm CMOS process. With NMCNR, it achieves a phase margin (PM) of 59° with a DC gain of 75 dB and unity-gain frequency (fug) of 712 MHz. With RNIC, the same four-stage amplifier achieves a phase margin of 84°, DC gain of 76 dB and fug of 2 GHz. Further, a three-stage single-ended amplifier is designed in a 1.1-V, 40-nm CMOS process. The three-stage OTA with RNIC achieves PM of 81°, DC gain of 80 dB and fug of 770 MHz. The same OTA achieves PM of 59° with NMCNR, while maintaining a DC gain of 75 dB and fug of 262 MHz. Pole-splitting, to achieve increased stability, is illustrated for both compensation schemes. Simulations illustrate that the RNIC scheme achieves much higher PM and fug for lower values of compensation capacitance compared to NMCNR, despite the growing number of low voltage amplifier stages.

  • 22.
    Ahmed, Mohammad Faisal
    et al.
    Cisco Syst India Private Ltd, India.
    Rajput, Kunwar Pritiraj
    Indian Inst Technol Kanpur, India; Univ Luxembourg, Luxembourg.
    Kumar Dasanadoddi Venkategowda, Naveen
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Fysik, elektroteknik och matematik. Linköpings universitet, Tekniska fakulteten.
    Jagannatham, Aditya K.
    Indian Inst Technol Kanpur, India.
    Hanzo, Lajos
    Univ Southampton, England.
    Privacy-Preserving Distributed Beamformer Design Techniques for Correlated Parameter Estimation2023Ingår i: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 23, nr 21, s. 26728-26739Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Privacy-preserving distributed beamforming designs are conceived for temporally correlated vector parameter estimation in an orthogonal frequency division multiplexing (OFDM)-based wireless sensor network (WSN). The temporal correlation inherent in the parameter vector is exploited by the rate distortion theory-based bit allocation framework used for the optimal quantization of the sensor measurements. The proposed distributed beamforming designs are derived via fusion of the dual consensus alternating direction method of multiplier (DC-ADMM) technique with a pertinent privacy-preserving framework. This makes it possible for each sensor node (SN) to design its transmit precoders in a distributed fashion, which minimizes the susceptibility of vital information to malicious eavesdropper (Ev) nodes, while simultaneously avoiding the significant communication overhead required by a centralized approach for the transmission of the state information to the fusion center (FC). The Bayesian Cramer-Rao bound (BCRB) is derived for benchmarking the estimation performance of the proposed transmit beamformer and receiver combiner designs, while our simulation results illustrate the performance and explicitly demonstrate the trade-off between the privacy and estimation performance.

  • 23.
    Ahmed, Mohammad Faisal
    et al.
    Cisco Systems Inc, Bangalore, Karnataka, India.
    Rajput, Kunwar Pritiraj
    Electrical engineering, Indian Institute of Technology Kanpur, Kanpur, UTTAR PRADESH, India.
    Venkategowda, Naveen
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Fysik, elektroteknik och matematik. Linköpings universitet, Tekniska fakulteten.
    Mishra, Kumar Vijay
    University of Iowa -IIHR, Iowa City, Iowa, United States.
    Jagannatham, Aditya K
    Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, Uttar Pradesh, India .
    Joint Transmit and Reflective Beamformer Design for Secure Estimation in IRS-Aided WSNs2022Ingår i: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 29, s. 692-696Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Wireless sensor networks (WSNs) are vulnerable to eavesdropping as the sensor nodes (SNs) communicate over an open radio channel. Intelligent reflecting surface (IRS) technology can be leveraged for physical layer security in WSNs. In this paper, we propose a joint transmit and reflective beamformer (JTRB) design for secure parameter estimation at the fusion center (FC) in the presence of an eavesdropper (ED) in a WSN. We develop a semidefinite relaxation (SDR)-based iterative algorithm, which alternately yields the transmit beamformer at each SN and the corresponding reflection phases at the IRS, to achieve the minimum mean-squared error (MSE) parameter estimate at the FC, subject to transmit power and ED signal-to-noise ratio constraints. Our simulation results demonstrate robust MSE and security performance of the proposed IRS-based JTRB technique.

  • 24.
    Aihara, Shin Ichi
    et al.
    Tokyo University of Science, Japan.
    Bagchi, Arunabha
    University of Twente, Enschede, Netherlands.
    Saha, Saikat
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Adaptive Filtering for Stochastic Volatility by Using Exact Sampling2013Ingår i: 10th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2013), 2013, s. 326-335Konferensbidrag (Refereegranskat)
    Abstract [en]

    We study the sequential identification problem for Bates stochastic volatility model, which is widely used as the model of a stock in finance. By using the exact simulation method, a particle filter for estimating stochastic volatility is constructed. The systems parameters are sequentially estimated with the aid of parallel filtering algorithm. To improve the estimation performance for unknown parameters, the new resampling procedure is proposed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.

  • 25.
    Akhlaghpasand, Hossein
    et al.
    Iran Univ Sci and Technol, Iran.
    Björnson, Emil
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Razavizadeh, S. Mohammad
    Iran Univ Sci and Technol, Iran.
    Jamming-Robust Uplink Transmission for Spatially Correlated Massive MIMO Systems2020Ingår i: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 68, nr 6, s. 3495-3504Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we consider how the uplink transmission of a spatially correlated massive multiple-input multiple-output (MIMO) system can be protected from a jamming attack. To suppress the jamming, we propose a novel framework including a new optimal linear estimator in the training phase and a bilinear equalizer in the data phase. The proposed estimator is optimal in the sense of maximizing the spectral efficiency of the legitimate system attacked by a jammer, and its implementation needs the statistical knowledge about the jammers channel. We derive an efficient algorithm to estimate the jamming information needed for implementation of the proposed framework. Furthermore, we demonstrate that optimized power allocation at the legitimate users can improve the performance of the proposed framework regardless of the jamming power optimization. Our proposed framework can be exploited to combat jamming in scenarios with either ideal or non-ideal hardware at the legitimate users and the jammer. Numerical results reveal that using the proposed framework, the jammer cannot dramatically affect the performance of the legitimate system.

  • 26.
    Akhlaghpasand, Hossein
    et al.
    Iran Univ Sci and Technol, Iran.
    Razavizadeh, S. Mohammad
    Iran Univ Sci and Technol, Iran.
    Björnson, Emil
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Do, Tan Tai
    Ericsson AB, Sweden.
    Jamming Detection in Massive MIMO Systems2018Ingår i: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, nr 2, s. 242-245Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This letter considers the physical layer security of a pilot-based massive multiple-input multiple-output (MaMIMO) system in presence of a multi-antenna jammer. We propose a new jamming detection method that makes use of a generalized likelihood ratio tes

  • 27.
    Akif, Ahmed
    Linköpings universitet, Institutionen för systemteknik, Datorteknik.
    FIR Filter Features on FPGA2018Självständigt arbete på grundnivå (högskoleexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Finite-length impulse response (FIR) filters are one of the most commonly used digital signal processing algorithms used nowadays where a FPGA is the device used to implement it. The continued development of the FPGA device through the insertion of dedicated blocks raised the need to study the advantages offered by different FPGA families. The work presented in this thesis study the special features offered by FPGAs for FIR filters and introduce a cost model of resource utilization. The used method consist of several stages including reading, classification of features and generating coefficients. The results show that FPGAs have common features but also specific differences in features as well as resource utilization. It has been shown that there is misconception when dealing with FPGAs when it comes to FIR filter as compared to ASICs.

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  • 28.
    Ala, Tirdad Seifi
    et al.
    Oticon AS, Denmark; Univ Nottingham, England.
    Alickovic, Emina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Oticon AS, Denmark.
    Cabrera, Alvaro Fuentes
    T&W Engn AS, Denmark.
    Whitmer, William M. M.
    Univ Nottingham, England.
    Hadley, Lauren V. V.
    Univ Nottingham, England.
    Rank, Mike L. L.
    T&W Engn AS, Denmark.
    Lunner, Thomas
    Oticon AS, Denmark.
    Graversen, Carina
    Oticon AS, Denmark.
    Alpha Oscillations During Effortful Continuous Speech: From Scalp EEG to Ear-EEG2023Ingår i: IEEE Transactions on Biomedical Engineering, ISSN 0018-9294, E-ISSN 1558-2531, Vol. 70, nr 4, s. 1264-1273Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: The purpose of this study was to investigate alpha power as an objective measure of effortful listening in continuous speech with scalp and ear-EEG. Methods: Scalp and ear-EEG were recorded simultaneously during presentation of a 33-s news clip in the presence of 16-talker babble noise. Four different signal-to-noise ratios (SNRs) were used to manipulate task demand. The effects of changes in SNR were investigated on alpha event-related synchronization (ERS) and desynchronization (ERD). Alpha activity was extracted from scalp EEG using different referencing methods (common average and symmetrical bi-polar) in different regions of the brain (parietal and temporal) and ear-EEG. Results: Alpha ERS decreased with decreasing SNR (i.e., increasing task demand) in both scalp and ear-EEG. Alpha ERS was also positively correlated to behavioural performance which was based on the questions regarding the contents of the speech. Conclusion: Alpha ERS/ERD is better suited to track performance of a continuous speech than listening effort. Significance: EEG alpha power in continuous speech may indicate of how well the speech was perceived and it can be measured with both scalp and Ear-EEG.

    Ladda ner fulltext (pdf)
    fulltext
  • 29.
    Alam, Syed Asad
    et al.
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Oscar
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Design of Finite Word Length Linear-Phase FIR Filters inthe Logarithmic Number System Domain2014Ingår i: VLSI design (Print), ISSN 1065-514X, E-ISSN 1563-5171, Vol. 2014, nr 217495Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Logarithmic number system (LNS) is an attractive alternative to realize finite-length impulse response filters because ofmultiplication in the linear domain being only addition in the logarithmic domain. In the literature, linear coefficients are directlyreplaced by the logarithmic equivalent. In this paper, an approach to directly optimize the finite word length coefficients in theLNS domain is proposed. This branch and bound algorithm is implemented based on LNS integers and several different branchingstrategies are proposed and evaluated. Optimal coefficients in the minimax sense are obtained and compared with the traditionalfinite word length representation in the linear domain as well as using rounding. Results show that the proposed method naturallyprovides smaller approximation error compared to rounding. Furthermore, they provide insights into finite word length propertiesof FIR filters coefficients in the LNS domain and show that LNS FIR filters typically provide a better approximation error comparedto a standard FIR filter.

    Ladda ner fulltext (pdf)
    AsadLNS_VLSIJ_Hindawi
  • 30.
    Alam, Syed Asad
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorteknik. Linköpings universitet, Tekniska fakulteten.
    Gustafsson, Oscar
    Linköpings universitet, Institutionen för systemteknik, Datorteknik. Linköpings universitet, Tekniska fakulteten.
    Generalized Division-Free Architecture and Compact Memory Structure for Resampling in Particle Filters2015Ingår i: 2015 European Conference on Circuit Theory and Design (ECCTD), IEEE Press, 2015, s. 416-419Konferensbidrag (Refereegranskat)
    Abstract [en]

    The most challenging step of implementing particle filtering is the resampling step which replicates particles with large weights and discards those with small weights. In this paper, we propose a generic architecture for resampling which uses double multipliers to avoid normalization divisions and make the architecture  equally efficient for non-powers-of-two number of particles. Furthermore, the complexity of resampling is greatly affected by the size of memories used to store weights. We illustrate that by storing the original weights instead of their cumulative sum and calculating them online reduces the total complexity, in terms of area, ranging from 21% to 45%, while giving up to 50% reduction in memory usage.

  • 31.
    Alam, Syed Asad
    et al.
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Gustafsson, Oscar
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem. Linköpings universitet, Tekniska högskolan.
    Implementation of Narrow-Band Frequency-Response Masking for Efficient Narrow Transition Band FIR Filters on FPGAs2011Ingår i: NORCHIP, 2011, IEEE conference proceedings, 2011, s. 1-4Konferensbidrag (Refereegranskat)
    Abstract [en]

    The complexity of narrow transition band FIR filters is highand can be reduced by using frequency response masking (FRM) techniques. Thesetechniques use a combination of periodic model filters and masking filters. Inthis paper, we show that time-multiplexed FRM filters achieve lowercomplexity, not only in terms of multipliers, but also logic elements compared to time-multiplexed singlestage filters. The reduced complexity also leads to a lower power consumption. Furthermore, we show that theoptimal period of the model filter is dependent on the time-multiplexing factor.

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    fulltext
  • 32.
    Alenlöv, Johan
    et al.
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Olsson, Jimmy
    Department of Mathematics, KTH Royal Institute of Technology, Stockholm, Sweden.
    Particle-based adaptive-lag online marginal smoothing in general state-space models2019Ingår i: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 67, nr 21, s. 5571-5582Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one for each marginal, in resemblance with the so-called particle-based, rapid incremental smoother (PaRIS). Each estimator is propagated until a stopping criterion, measuring the fluctuations of the estimates, is met. The presented algorithm is furnished with theoretical results describing its asymptotic limit and memory usage.

  • 33.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Subasi, Abdulhamit
    Effat Univ, Saudi Arabia.
    Ensemble SVM Method for Automatic Sleep Stage Classification2018Ingår i: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 67, nr 6, s. 1258-1265Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Sleep scoring is used as a diagnostic technique in the diagnosis and treatment of sleep disorders. Automated sleep scoring is crucial, since the large volume of data should be analyzed visually by the sleep specialists which is burdensome, time-consuming tedious, subjective, and error prone. Therefore, automated sleep stage classification is a crucial step in sleep research and sleep disorder diagnosis. In this paper, a robust system, consisting of three modules, is proposed for automated classification of sleep stages from the single-channel electroencephalogram (EEG). In the first module, signals taken from Pz-Oz electrode were denoised using multiscale principal component analysis. In the second module, the most informative features are extracted using discrete wavelet transform (DWT), and then, statistical values of DWT subbands are calculated. In the third module, extracted features were fed into an ensemble classifier, which can be called as rotational support vector machine (RotSVM). The proposed classifier combines advantages of the principal component analysis and SVM to improve classification performances of the traditional SVM. The sensitivity and accuracy values across all subjects were 84.46% and 91.1%, respectively, for the five-stage sleep classification with Cohens kappa coefficient of 0.88. Obtained classification performance results indicate that, it is possible to have an efficient sleep monitoring system with a single-channel EEG, and can be used effectively in medical and home-care applications.

    Ladda ner fulltext (pdf)
    fulltext
  • 34.
    Almqvist, Erik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Airborne mapping using LIDAR2010Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Kartering är ett centralt och vanligt förekommande problem inom robotik. Att bygga en korrekt karta av en robots omgivning utan mänsklig hjälp har en mängd tänkbara användningsområden. Exempel på sådana är rymduppdrag, räddningsoperationer,övervakning och användning i områden som är farliga för människor. En tillämpning för robotkartering är att mäta volymökning hos terräng över tiden. I Sverige finns det över hundra soptippar, och dessa soptippar är reglerade av lagar som säger att man måste mäta soptippens volymökning minst en gång om året.

    I detta exjobb görs en undersökning av möjligheterna att göra dessa volymberäkningarmed hjälp av obemannade helikoptrar utrustade med en Light Detectionand Ranging (LIDAR) sensor. Olika tekniker har testats, både tekniker som slår ihop LIDAR data till en karta och regressionstekniker baserade på Gauss Processer. I avsaknad av data inspelad med riktig helikopter har ett experiment med en industri robot genomförts för att samla in data. Resultaten av volymmätningarnavar goda i förhållande till LIDAR-sensorns upplösning. För att få bättre volymmätningaroch bättre utvärderingar av de olika algoritmerna är en bättre LIDAR-sensor nödvändig.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 35.
    Almér, Louise
    Linköpings universitet, Institutionen för systemteknik, Informationskodning.
    Evaluation of the Perceived Speech Quality for G729D and Opus: With Different Network Scenarios and an Implemented VoIP Application2022Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Communication has always been a vital part of our society, and day-to-day communication is increasingly becoming more digital. VoIP (voice over IP) is used for real-time communication, and to be able to send the information over the internet must the speech be compressed to lower the number of bits needed for transmission. Codecs are used to compress the speech, or any other type of data transmitting over a network, which can introduce some noise if lossy compression is used. Depending on the bandwidth, bit rate, and codec used can distortion be minimized which would result in higher perceived speech quality.

    In the thesis, two codecs, G729D and Opus, were tested and evaluated with two different objective perceive speech quality metrics, POLQA and PESQ. The codecs were also tested with different emulated network scenarios, 2G, 3G, 4G, satellite two-hop, and LAN. Furthermore, Opus was tested with and without VAD (voice activity detection) to see how VAD could affect the perceived speech quality. The different network scenarios did not impact the results of the evaluation, since the main difference between the network scenarios was latency, which POLQA and PESQ do not consider in the evaluation. Opus achieved a higher MOS-LQO (mean opinion score listening quality objective) than G729D. However, when VAD was enabled with Opus for a low bit rate, 8 kbit/s, the MOS-LQO was lower than without VAD. 

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  • 36.
    Alwan, Abdulrahman
    Linköpings universitet, Institutionen för systemteknik, Informationskodning.
    Implementation of Wavelet-Kalman Filtering Technique for Auditory Brainstem Response2012Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Auditory brainstem response (ABR) evaluation has been one of the most reliable methods for evaluating hearing loss. Clinically available methods for ABR tests require averaging for a large number of sweeps (~1000-2000) in order to obtain a meaningful ABR signal, which is time consuming.  This study proposes a faster new method for ABR filtering based on wavelet-Kalman filter that is able to produce a meaningful ABR signal with less than 500 sweeps. The method is validated against ABR data acquired from 7 normal hearing subjects with different stimulus intensity levels, the lowest being 30 dB NHL. The proposed method was able to filter and produce a readable ABR signal using 400 sweeps; other ABR signal criteria were also presented to validate the performance of the proposed method.

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    fulltext
  • 37.
    Andersson, Erik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem.
    Olsson, Christian
    Linköpings universitet, Institutionen för systemteknik, Elektroniksystem.
    Linearization of Power Amplifier using Digital Predistortion, Implementation on FPGA2014Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    The purpose of this thesis is to linearize a power amplifier using digital predistortion. A power amplifier is a nonlinear system, meaning that when fed with a pure input signal the output will be distorted. The idea behind digital predistortion is to distort the signal before feeding it to the power amplifier. The combined distortions from the predistorter and the power amplifier will then ideally cancel each other. In this thesis, two different approaches are investigated and implemented on an FPGA. The first approach uses a nonlinear model that tries to cancel out the nonlinearities of the power amplifier. The second approach is model-free and instead makes use of a look-up table that maps the input to a distorted output. Both approaches are made adaptive so that the parameters are continuously updated using adaptive algorithms. First the two approaches are simulated and tested thoroughly with different parameters and with a power amplifier model extracted from the real amplifier. The results are shown satisfactory in the simulations, giving good linearization for both the model and the model-free technique. The two techniques are then implemented on an FPGA and tested on the power amplifier. Even though the results are not as well as in the simulations, the system gets more linear for both the approaches. The results vary widely due to different circumstances such as input frequency and power. Typically, the distortions can be attenuated with around 10 dB. When comparing the two techniques with each other, the model-free method shows slightly better results.

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    fulltext
  • 38.
    Andersson, Fredrik
    Linköpings universitet, Institutionen för systemteknik.
    Determining recording time of digital soundrecordings using the ENF criterion2009Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats
    Abstract [en]

    In forensic investigations, verification of digital recordings is an important as-pect. There are numerous methods to verify authentication of recordings, but itis difficult to determine when the media was recorded. By studying the electricalnetwork frequency, one can find a unique signature and then match the recordingto this signature. By matching a recorded signal to a database, which contains allnecessary information, one can find the time when the recording was made.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 39.
    Andersson Granberg, Tobias
    et al.
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    Jonson, Carl-Oscar
    Linköpings universitet, Institutionen för biomedicinska och kliniska vetenskaper, Avdelningen för kirurgi, ortopedi och onkologi. Linköpings universitet, Medicinska fakulteten. Region Östergötland, Regionledningskontoret, Katastrofmedicinskt centrum.
    Prytz, Erik
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Filosofiska fakulteten.
    Steins, Krisjanis
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    Waldemarsson, Martin
    Linköpings universitet, Institutionen för teknik och naturvetenskap, Kommunikations- och transportsystem. Linköpings universitet, Tekniska fakulteten.
    Sensor Requirements for Logistics Analysis of Emergency Incident Sites2020Ingår i: Proceedings of the 17th ISCRAM Conference / [ed] Amanda Lee Hughes, Fiona McNeill, Christopher Zobe, Information Systems for Crisis Response and Management , 2020, s. 952-960Konferensbidrag (Refereegranskat)
    Abstract [en]

    Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.

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    fulltext
  • 40.
    Andersson, Håkan
    Linköpings universitet, Institutionen för systemteknik. Linköpings universitet, Tekniska högskolan.
    Error-Correcting Codes Based on Chaotic Dynamical Systems1998Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    This dissertation treats a novel class of error-correcting codes based on chaotic dynamical systems. The codes are defined over a continuous alphabet whereas the information that is to be transmitted belongs to a discrete set of symbols. Simple expressions can be given for the encoders, and the codewords can be described by a parity-check relation. However, the most interesting approach is to view the codewords as orbits of iterated dynamical systems described by integer matrices.

    Under some rather natural assumptions, the codes are shown to be group codes. The minimum distance is proved to be well-defined and strictly greater than zero. An algorithm for calculating it is also given. Initially, no robust sliding-window encoder inverses exist, but this deficiency is remedied by the introduction of fractal signal sets. The problem of catastrophic encoders is also solved by the introduction of these totally disconnected signal sets.

    Decoding strategies are discussed, and it is shown why the Viterbi algorithm does not work in higher dimensions for this type of codes. So-called list decoding emerges as a good alternative and its merits are considered. Simulations and comparisons with binary antipodal signaling are performed. The setting of the work is in two dimensions. However, the strength of this code construction is that it easily generalizes to higher dimensions.

  • 41.
    Andersson, Kenneth
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Westin, Carl-Fredrik
    Laboratory of Mathematics in Imaging, Harvard Medical School, Brigham and Women's Hospital, Boston, USA.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska högskolan.
    Prediction from off-grid samples using continuous normalized convolution2007Ingår i: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 87, nr 3, s. 353-365Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.

  • 42.
    Andersson, Martin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Kommunikationssystem. Linköpings universitet, Tekniska fakulteten.
    Lidström, Andreas
    Linköpings universitet.
    Lindmark, Gustav
    Ericsson AB, Linkoping, Sweden.
    Indoor 5G Positioning using Multipath Measurements2023Ingår i: 2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS, IEEE , 2023, s. 1092-1098Konferensbidrag (Refereegranskat)
    Abstract [en]

    Positioning with high precision and reliability can be provided by 5G cellular networks in environments where satellite positioning is not available or reliable. The accuracy that can be achieved by classical methods like triangulation and trilateration however degrades significantly under non line of sight (NLOS) conditions. The problem can be mitigated with increasingly dense deployments of network transmission and reception points (TRPs), but that is both impractical and costly. As an alternative, this study investigates if multipath propagation of radio signals can be exploited to improve positioning accuracy and reduce the necessary deployment density. With 3GPP Rel. 17 new signaling support has been introduced to report the propagation delay, corresponding to the length, of multiple paths between the user equipment (UE) and a network TRP. The length of a multipath can, in combination with a partially known map of the environment, give additional information about the UE position. In this study we develop multipath-assisted tracking algorithms and evaluate their performances in realistic simulations using 3GPP standardized positioning reference signals and measurements in an indoor factory environment. Our evaluations show that multipath-assisted algorithms can achieve an accuracy below 0.9 m in 90% of the cases, which is more than tenfold better than a conventional LOS based algorithm. Moreover, one algorithm variant also shows an ability to track a UE using very few TRPs.

  • 43.
    Andersson, Mats
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Burdakov, Oleg
    Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Zikrin, Spartak
    Linköpings universitet, Matematiska institutionen. Linköpings universitet, Tekniska högskolan.
    Sparsity Optimization in Design of Multidimensional Filter Networks2013Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Filter networks is a powerful tool used for reducing the image processing time, while maintaining its reasonably high quality.They are composed of sparse sub-filters whose low sparsity ensures fast image processing.The filter network design is related to solvinga sparse optimization problem where a cardinality constraint bounds above the sparsity level.In the case of sequentially connected sub-filters, which is the simplest network structure of those considered in this paper, a cardinality-constrained multilinear least-squares (MLLS) problem is to be solved. If to disregard the cardinality constraint, the MLLS is typically a large-scale problem characterized by a large number of local minimizers. Each of the local minimizers is singular and non-isolated.The cardinality constraint makes the problem even more difficult to solve.An approach for approximately solving the cardinality-constrained MLLS problem is presented.It is then applied to solving a bi-criteria optimization problem in which both thetime and quality of image processing are optimized. The developed approach is extended to designing filter networks of a more general structure. Its efficiency is demonstrated by designing certain 2D and 3D filter networks. It is also compared with the existing approaches.

    Ladda ner fulltext (pdf)
    Sparsity Optimization in Design of Multidimensional Filter Networks (revised version)
  • 44. Beställ onlineKöp publikationen >>
    Andersson Naesseth, Christian
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Machine learning using approximate inference: Variational and sequential Monte Carlo methods2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Automatic decision making and pattern recognition under uncertainty are difficult tasks that are ubiquitous in our everyday life. The systems we design, and technology we develop, requires us to coherently represent and work with uncertainty in data. Probabilistic models and probabilistic inference gives us a powerful framework for solving this problem. Using this framework, while enticing, results in difficult-to-compute integrals and probabilities when conditioning on the observed data. This means we have a need for approximate inference, methods that solves the problem approximately using a systematic approach. In this thesis we develop new methods for efficient approximate inference in probabilistic models.

    There are generally two approaches to approximate inference, variational methods and Monte Carlo methods. In Monte Carlo methods we use a large number of random samples to approximate the integral of interest. With variational methods, on the other hand, we turn the integration problem into that of an optimization problem. We develop algorithms of both types and bridge the gap between them.

    First, we present a self-contained tutorial to the popular sequential Monte Carlo (SMC) class of methods. Next, we propose new algorithms and applications based on SMC for approximate inference in probabilistic graphical models. We derive nested sequential Monte Carlo, a new algorithm particularly well suited for inference in a large class of high-dimensional probabilistic models. Then, inspired by similar ideas we derive interacting particle Markov chain Monte Carlo to make use of parallelization to speed up approximate inference for universal probabilistic programming languages. After that, we show how we can make use of the rejection sampling process when generating gamma distributed random variables to speed up variational inference. Finally, we bridge the gap between SMC and variational methods by developing variational sequential Monte Carlo, a new flexible family of variational approximations.

    Delarbeten
    1. Capacity estimation of two-dimensional channels using Sequential Monte Carlo
    Öppna denna publikation i ny flik eller fönster >>Capacity estimation of two-dimensional channels using Sequential Monte Carlo
    2014 (Engelska)Ingår i: 2014 IEEE Information Theory Workshop, 2014, s. 431-435Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    We derive a new Sequential-Monte-Carlo-based algorithm to estimate the capacity of two-dimensional channel models. The focus is on computing the noiseless capacity of the 2-D (1, ∞) run-length limited constrained channel, but the underlying idea is generally applicable. The proposed algorithm is profiled against a state-of-the-art method, yielding more than an order of magnitude improvement in estimation accuracy for a given computation time.

    Nationell ämneskategori
    Reglerteknik Datavetenskap (datalogi) Sannolikhetsteori och statistik
    Identifikatorer
    urn:nbn:se:liu:diva-112966 (URN)10.1109/ITW.2014.6970868 (DOI)
    Konferens
    Information Theory Workshop
    Tillgänglig från: 2015-01-06 Skapad: 2015-01-06 Senast uppdaterad: 2018-11-09
    2. Sequential Monte Carlo for Graphical Models
    Öppna denna publikation i ny flik eller fönster >>Sequential Monte Carlo for Graphical Models
    2014 (Engelska)Ingår i: Advances in Neural Information Processing Systems, 2014, s. 1862-1870Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    We propose a new framework for how to use sequential Monte Carlo (SMC) algorithms for inference in probabilistic graphical models (PGM). Via a sequential decomposition of the PGM we find a sequence of auxiliary distributions defined on a monotonically increasing sequence of probability spaces. By targeting these auxiliary distributions using SMC we are able to approximate the full joint distribution defined by the PGM. One of the key merits of the SMC sampler is that it provides an unbiased estimate of the partition function of the model. We also show how it can be used within a particle Markov chain Monte Carlo framework in order to construct high-dimensional block-sampling algorithms for general PGMs.

    Nationell ämneskategori
    Datavetenskap (datalogi) Sannolikhetsteori och statistik Reglerteknik
    Identifikatorer
    urn:nbn:se:liu:diva-112967 (URN)
    Konferens
    Neural Information Processing Systems (NIPS)
    Tillgänglig från: 2015-01-06 Skapad: 2015-01-06 Senast uppdaterad: 2018-11-09Bibliografiskt granskad
    3. Nested Sequential Monte Carlo Methods
    Öppna denna publikation i ny flik eller fönster >>Nested Sequential Monte Carlo Methods
    2015 (Engelska)Ingår i: Proceedings of The 32nd International Conference on Machine Learning / [ed] Francis Bach, David Blei, Journal of Machine Learning Research (Online) , 2015, Vol. 37, s. 1292-1301Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    We propose nested sequential Monte Carlo (NSMC), a methodology to sample from sequences of probability distributions, even where the random variables are high-dimensional. NSMC generalises the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correct SMC algorithm. Furthermore, NSMC can in itself be used to produce such properly weighted samples. Consequently, one NSMC sampler can be used to construct an efficient high-dimensional proposal distribution for another NSMC sampler, and this nesting of the algorithm can be done to an arbitrary degree. This allows us to consider complex and high-dimensional models using SMC. We show results that motivate the efficacy of our approach on several filtering problems with dimensions in the order of 100 to 1 000.

    Ort, förlag, år, upplaga, sidor
    Journal of Machine Learning Research (Online), 2015
    Serie
    JMLR Workshop and Conference Proceedings, ISSN 1938-7288 ; 37
    Nationell ämneskategori
    Datavetenskap (datalogi) Reglerteknik Sannolikhetsteori och statistik
    Identifikatorer
    urn:nbn:se:liu:diva-122698 (URN)2-s2.0-84969760860 (Scopus ID)9781510810587 (ISBN)
    Konferens
    32nd International Conference on Machine Learning, Lille, France, 6-11 July, 2015
    Tillgänglig från: 2015-11-16 Skapad: 2015-11-16 Senast uppdaterad: 2024-04-25Bibliografiskt granskad
    4. Interacting Particle Markov Chain Monte Carlo
    Öppna denna publikation i ny flik eller fönster >>Interacting Particle Markov Chain Monte Carlo
    Visa övriga...
    2016 (Engelska)Ingår i: Proceedings of the 33rd International Conference on Machine Learning (ICML), 2016, Vol. 48, s. 2616-2625Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    We introduce interacting particle Markov chain Monte Carlo (iPMCMC), a PMCMC method based on an interacting pool of standard and conditional sequential Monte Carlo samplers. Like related methods, iPMCMC is a Markov chain Monte Carlo sampler on an extended space. We present empirical results that show significant improvements in mixing rates relative to both non-interacting PMCMC samplers and a single PMCMC sampler with an equivalent memory and computational budget. An additional advantage of the iPMCMC method is that it is suitable for distributed and multi-core architectures.

    Serie
    Proceedings of Machine Learning Research, ISSN 2640-3498 ; 48
    Nyckelord
    Sequential Monte Carlo, Probabilistic programming, parallelisation
    Nationell ämneskategori
    Datavetenskap (datalogi) Reglerteknik Sannolikhetsteori och statistik
    Identifikatorer
    urn:nbn:se:liu:diva-130043 (URN)
    Konferens
    International Conference on Machine Learning (ICML), New York, USA, June 19-24, 2016
    Projekt
    CADICS
    Forskningsfinansiär
    Cancer- och Allergifonden
    Tillgänglig från: 2016-07-05 Skapad: 2016-07-05 Senast uppdaterad: 2022-03-01Bibliografiskt granskad
    5. Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
    Öppna denna publikation i ny flik eller fönster >>Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
    2017 (Engelska)Ingår i: Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, PMLR , 2017Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    Variational inference using the reparameterization trick has enabled large-scale approximate Bayesian inference in complex probabilistic models, leveraging stochastic optimization to sidestep intractable expectations. The reparameterization trick is applicable when we can simulate a random variable by applying a differentiable deterministic function on an auxiliary random variable whose distribution is fixed. For many distributions of interest (such as the gamma or Dirichlet), simulation of random variables relies on acceptance-rejection sampling. The discontinuity introduced by the accept-reject step means that standard reparameterization tricks are not applicable. We propose a new method that lets us leverage reparameterization gradients even when variables are outputs of a acceptance-rejection sampling algorithm. Our approach enables reparameterization on a larger class of variational distributions. In several studies of real and synthetic data, we show that the variance of the estimator of the gradient is significantly lower than other state-of-the-art methods. This leads to faster convergence of stochastic gradient variational inference.

    Ort, förlag, år, upplaga, sidor
    PMLR, 2017
    Serie
    JMLR workshop and conference proceedings, ISSN 1938-7288 ; 54
    Nationell ämneskategori
    Datavetenskap (datalogi)
    Identifikatorer
    urn:nbn:se:liu:diva-152645 (URN)000509368500053 ()
    Konferens
    Artificial Intelligence and Statistics, 20-22 April 2017, Fort Lauderdale, FL, USA
    Tillgänglig från: 2018-11-09 Skapad: 2018-11-09 Senast uppdaterad: 2024-04-25Bibliografiskt granskad
    6. Variational Sequential Monte Carlo
    Öppna denna publikation i ny flik eller fönster >>Variational Sequential Monte Carlo
    2018 (Engelska)Ingår i: Proceedings of International Conference on Artificial Intelligence and Statistics, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands / [ed] Amos Storkey and Fernando Perez-Cruz, PMLR , 2018, Vol. 84, s. 968-977Konferensbidrag, Publicerat paper (Refereegranskat)
    Abstract [en]

    Many recent advances in large scale probabilistic inference rely on variational methods. The success of variational approaches depends on (i) formulating a flexible parametric family of distributions, and (ii) optimizing the parameters to find the member of this family that most closely approximates the exact posterior. In this paper we present a new approximating family of distributions, the variational sequential Monte Carlo (VSMC) family, and show how to optimize it in variational inference. VSMC melds variational inference (VI) and sequential Monte Carlo (SMC), providing practitioners with flexible, accurate, and powerful Bayesian inference. The VSMC family is a variational family that can approximate the posterior arbitrarily well, while still allowing for efficient optimization of its parameters. We demonstrate its utility on state space models, stochastic volatility models for financial data, and deep Markov models of brain neural circuits.

    Ort, förlag, år, upplaga, sidor
    PMLR, 2018
    Serie
    Proceedings of Machine Learning Research, ISSN 2640-3498 ; 84
    Nationell ämneskategori
    Datavetenskap (datalogi)
    Identifikatorer
    urn:nbn:se:liu:diva-152646 (URN)000509385300102 ()2-s2.0-85057232074 (Scopus ID)
    Konferens
    The 21st International Conference on Artificial Intelligence and Statistics, Playa Blanca, Lanzarote, Canary Islands, April 9-11, 2018
    Tillgänglig från: 2018-11-09 Skapad: 2018-11-09 Senast uppdaterad: 2024-02-01Bibliografiskt granskad
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    Machine learning using approximate inference: Variational and sequential Monte Carlo methods
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  • 45.
    Andersson Naesseth, Christian
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Vision and Radar Sensor Fusion for Advanced Driver Assistance Systems2013Självständigt arbete på avancerad nivå (yrkesexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    The World Health Organization predicts that by the year 2030, road traffic injuries will be one of the top five leading causes of death. Many of these deaths and injuries can be prevented by driving cars properly equipped with state-of-the-art safety and driver assistance systems. Some examples are auto-brake and auto-collision avoidance which are becoming more and more popular on the market today. A recent study by a Swedish insurance company has shown that on roadswith speeds up to 50 km/h an auto-brake system can reduce personal injuries by up to 64 percent. In fact in an estimated 40 percent of crashes, the auto-brake reduced the effects to the degree that no personal injury was sustained.

    It is imperative that these so called Advanced Driver Assistance Systems, to be really effective, have good situational awareness. It is important that they have adequate information of the vehicle’s immediate surroundings. Where are other cars, pedestrians or motorcycles relative to our own vehicle? How fast are they driving and in which lane? How is our own vehicle driving? Are there objects in the way of our own vehicle’s intended path? These and many more questions can be answered by a properly designed system for situational awareness.

    In this thesis we design and evaluate, both quantitatively and qualitatively, sensor fusion algorithms for multi-target tracking. We use a combination of camera and radar information to perform fusion and find relevant objects in a cluttered environment. The combination of these two sensors is very interesting because of their complementary attributes. The radar system has high range resolution but poor bearing resolution. The camera system on the other hand has a very high bearing resolution. This is very promising, with the potential to substantially increase the accuracy of the tracking system compared to just using one of the two. We have also designed algorithms for path prediction and a first threat awareness logic which are both qualitively evaluated.

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  • 46.
    Andersson, Thord
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska högskolan.
    Läthén, Gunnar
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Lenz, Reiner
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för teknik och naturvetenskap, Medie- och Informationsteknik. Linköpings universitet, Tekniska högskolan.
    Borga, Magnus
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Modified Gradient Search for Level Set Based Image Segmentation2013Ingår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 22, nr 2, s. 621-630Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general nonconvex functionals. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functionals have been modified to avoid these problems. In this paper, we instead propose using two modified gradient descent methods, one using a momentum term and one based on resilient propagation. These methods are commonly used in the machine learning community. In a series of 2-D/3-D-experiments using real and synthetic data with ground truth, the modifications are shown to reduce the sensitivity for local optima and to increase the convergence rate. The parameter sensitivity is also investigated. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. Downloadable reference code with examples is available online.

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  • 47.
    Andersson, Viktor
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Semantic Segmentation: Using Convolutional Neural Networks and Sparse dictionaries2017Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    The two main bottlenecks using deep neural networks are data dependency and training time. This thesis proposes a novel method for weight initialization of the convolutional layers in a convolutional neural network. This thesis introduces the usage of sparse dictionaries. A sparse dictionary optimized on domain specific data can be seen as a set of intelligent feature extracting filters. This thesis investigates the effect of using such filters as kernels in the convolutional layers in the neural network. How do they affect the training time and final performance?

    The dataset used here is the Cityscapes-dataset which is a library of 25000 labeled road scene images.The sparse dictionary was acquired using the K-SVD method. The filters were added to two different networks whose performance was tested individually. One of the architectures is much deeper than the other. The results have been presented for both networks. The results show that filter initialization is an important aspect which should be taken into consideration while training the deep networks for semantic segmentation.

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  • 48.
    Andreu-Cabedo, Yasmina
    et al.
    University of Central Lancashire, England.
    Castellano, Pedro
    University of Central Lancashire, England.
    Colantonio, Sara
    National Research Council Italy, Italy.
    Coppini, Giuseppe
    National Research Council Italy, Italy.
    Favilla, Riccardo
    National Research Council Italy, Italy.
    Germanese, Danila
    National Research Council Italy, Italy.
    Giannakakis, Giorgos
    Fdn Research and Technology, Greece.
    Giorgi, Daniela
    National Research Council Italy, Italy.
    Larsson, Marcus
    Linköpings universitet, Institutionen för medicinsk teknik, Biomedicinsk instrumentteknik. Linköpings universitet, Tekniska fakulteten.
    Marraccini, Paolo
    National Research Council Italy, Italy.
    Martinelli, Massimo
    National Research Council Italy, Italy.
    Matuszewski, Bogdan
    University of Central Lancashire, England.
    Milanic, Matijia
    Norvegian University of Science and Technology, Norway.
    Pascali, Mariantonietta
    National Research Council Italy, Italy.
    Pediaditis, Mattew
    Fdn Research and Technology, Greece.
    Raccichini, Giovanni
    National Research Council Italy, Italy.
    Randeberg, Lise
    Norvegian University of Science and Technology, Norway.
    Salvetti, Ovidio
    National Research Council Italy, Italy.
    Strömberg, Tomas
    Linköpings universitet, Institutionen för medicinsk teknik, Biomedicinsk instrumentteknik. Linköpings universitet, Tekniska fakulteten.
    MIRROR MIRROR ON THE WALL... AN INTELLIGENT MULTISENSORY MIRROR FOR WELL-BEING SELF-ASSESSMENT2015Ingår i: 2015 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA and EXPO (ICME), IEEE , 2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    The face reveals the healthy status of an individual, through a combination of physical signs and facial expressions. The project SEMEOTICONS is translating the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, images, and 3D scans of the face. SEMEOTICONS is developing a multisensory platform, in the form of a smart mirror, looking for signs related to cardio-metabolic risk. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. Building the multisensory mirror requires addressing significant scientific and technological challenges, from touch-less data acquisition, to real-time processing and integration of multimodal data.

  • 49.
    Antonsson, Per
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Johansson, Jesper
    Linköpings universitet, Institutionen för systemteknik, Datorseende.
    Measuring Respiratory Frequency Using Optronics and Computer Vision2021Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    This thesis investigates the development and use of software to measure respiratory frequency on cows using optronics and computer vision. It examines mainly two different strategies of image and signal processing and their performances for different input qualities. The effect of heat stress on dairy cows and the high transmission risk of pneumonia for calves make the investigation done during this thesis highly relevant since they both have the same symptom; increased respiratory frequency. The data set used in this thesis was of recorded dairy cows in different environments and from varying angles. Recordings, where the authors could determine a true breathing frequency by monitoring body movements, were accepted to the data set and used to test and develop the algorithms. One method developed in this thesis estimated the breathing rate in the frequency domain by Fast Fourier Transform and was named "N-point Fast Fourier Transform." The other method was called "Breathing Movement Zero-Crossing Counting." It estimated a signal in the time domain, whose fundamental frequency was determined by a zero-crossing algorithm as the breathing frequency. The result showed that both the developed algorithm successfully estimated a breathing frequency with a reasonable error margin for most of the data set. The zero-crossing algorithm showed the most consistent result with an error margin lower than 0.92 breaths per minute (BPM) for twelve of thirteen recordings. However, it is limited to recordings where the camera is placed above the cow. The N-point FFT algorithm estimated the breathing frequency with error margins between 0.44 and 5.20 BPM for the same recordings as the zero-crossing algorithm. This method is not limited to a specific camera angle but requires the cow to be relatively stationary to get accurate results. Therefore, it could be evaluated with the remaining three recordings of the data set. The error margins for these recordings were measured between 1.92 and 10.88 BPM. Both methods had execution time acceptable for implementation in real-time. It was, however, too incomplete a data set to determine any performance with recordings from different optronic devices. 

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  • 50. Beställ onlineKöp publikationen >>
    Ardeshiri, Tohid
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Analytical Approximations for Bayesian Inference2015Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Bayesian inference is a statistical inference technique in which Bayes’ theorem is used to update the probability distribution of a random variable using observations. Except for few simple cases, expression of such probability distributions using compact analytical expressions is infeasible. Approximation methods are required to express the a priori knowledge about a random variable in form of prior distributions. Further approximations are needed to compute posterior distributions of the random variables using the observations. When the computational complexity of representation of such posteriors increases over time as in mixture models, approximations are required to reduce the complexity of such representations.

    This thesis further extends existing approximation methods for Bayesian inference, and generalizes the existing approximation methods in three aspects namely; prior selection, posterior evaluation given the observations and maintenance of computation complexity.

    Particularly, the maximum entropy properties of the first-order stable spline kernel for identification of linear time-invariant stable and causal systems are shown. Analytical approximations are used to express the prior knowledge about the properties of the impulse response of a linear time-invariant stable and causal system.

    Variational Bayes (VB) method is used to compute an approximate posterior in two inference problems. In the first problem, an approximate posterior for the state smoothing problem for linear statespace models with unknown and time-varying noise covariances is proposed. In the second problem, the VB method is used for approximate inference in state-space models with skewed measurement noise.

    Moreover, a novel approximation method for Bayesian inference is proposed. The proposed Bayesian inference technique is based on Taylor series approximation of the logarithm of the likelihood function. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions.

    Finally, two contributions are dedicated to the mixture reduction (MR) problem. The first contribution, generalize the existing MR algorithms for Gaussian mixtures to the exponential family of distributions and compares them in an extended target tracking scenario. The second contribution, proposes a new Gaussian mixture reduction algorithm which minimizes the reverse Kullback-Leibler divergence and has specific peak preserving properties.

    Delarbeten
    1. Maximum entropy properties of discrete-time first-order stable spline kernel
    Öppna denna publikation i ny flik eller fönster >>Maximum entropy properties of discrete-time first-order stable spline kernel
    Visa övriga...
    2016 (Engelska)Ingår i: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 66, s. 34-38Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    The first order stable spline (SS-1) kernel (also known as the tunedcorrelated kernel) is used extensively in regularized system identification, where the impulse response is modeled as a zero-mean Gaussian process whose covariance function is given by well designed and tuned kernels. In this paper, we discuss the maximum entropy properties of this kernel. In particular, we formulate the exact maximum entropy problem solved by the SS-1 kernel without Gaussian and uniform sampling assumptions. Under general sampling assumption, we also derive the special structure of the SS-1 kernel (e.g. its tridiagonal inverse and factorization have closed form expression), also giving to it a maximum entropy covariance completion interpretation.

    Nyckelord
    System identification;Regularization method;Kernel structure;Maximum entropy
    Nationell ämneskategori
    Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-121618 (URN)10.1016/j.automatica.2015.12.009 (DOI)
    Tillgänglig från: 2015-09-28 Skapad: 2015-09-28 Senast uppdaterad: 2024-01-08Bibliografiskt granskad
    2. Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances
    Öppna denna publikation i ny flik eller fönster >>Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances
    2015 (Engelska)Ingår i: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, nr 12, s. 2450-2454Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    We present an adaptive smoother for linear state-space models with unknown process and measurement noise covariances. The proposed method utilizes the variational Bayes technique to perform approximate inference. The resulting smoother is computationally efficient, easy to implement, and can be applied to high dimensional linear systems. The performance of the algorithm is illustrated on a target tracking example.

    Ort, förlag, år, upplaga, sidor
    Institute of Electrical and Electronics Engineers (IEEE), 2015
    Nyckelord
    Adaptive smoothing, Kalman filtering, noise covariance, Rauch-Tung-Striebel smoother, sensor calibration, time-varying noiseco variances, variational Bayes
    Nationell ämneskategori
    Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-121617 (URN)10.1109/LSP.2015.2490543 (DOI)000364207300007 ()
    Anmärkning

    At the time for thesis presentation publication was in status: Manuscript

    Tillgänglig från: 2015-09-28 Skapad: 2015-09-28 Senast uppdaterad: 2018-03-09Bibliografiskt granskad
    3. Robust Inference for State-Space Models with Skewed Measurement Noise
    Öppna denna publikation i ny flik eller fönster >>Robust Inference for State-Space Models with Skewed Measurement Noise
    2015 (Engelska)Ingår i: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, nr 11, s. 1898-1902Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    Filtering and smoothing algorithms for linear discrete-time state-space models with skewed and heavy-tailed measurement noise are presented. The algorithms use a variational Bayes approximation of the posterior distribution of models that have normal prior and skew-t-distributed measurement noise. The proposed filter and smoother are compared with conventional low-complexity alternatives in a simulated pseudorange positioning scenario. In the simulations the proposed methods achieve better accuracy than the alternative methods, the computational complexity of the filter being roughly 5 to 10 times that of the Kalman filter.

    Ort, förlag, år, upplaga, sidor
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2015
    Nyckelord
    Kalman filter; robust filtering; RTS smoother; skew t; skewness; t-distribution; variational Bayes
    Nationell ämneskategori
    Elektroteknik och elektronik
    Identifikatorer
    urn:nbn:se:liu:diva-120129 (URN)10.1109/LSP.2015.2437456 (DOI)000356458700003 ()
    Anmärkning

    Funding Agencies|Tampere University of Technology Graduate School; Finnish Doctoral Programme in Computational Sciences (FICS); Foundation of Nokia Corporation; Swedish research council (VR), project ETT [621-2010-4301]

    Tillgänglig från: 2015-07-14 Skapad: 2015-07-13 Senast uppdaterad: 2017-12-04
    4. Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family
    Öppna denna publikation i ny flik eller fönster >>Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family
    (Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    In this paper, a Bayesian inference technique based on Taylor series approximation of the logarithm of the likelihood function is presented. The proposed approximation is devised for the case where the prior distribution belongs to the exponential family of distributions. The logarithm of the likelihood function is linearized with respect to the sufficient statistic of the prior distribution in exponential family such that the posterior obtains the same exponential family form as the prior. Similarities between the proposed method and the extended Kalman filter for nonlinear filtering are illustrated. Further, an extended target measurement update for target models where the target extent is represented by a random matrix having an inverse Wishart distribution is derived. The approximate update covers the important case where the spread of measurement is due to the target extent as well as the measurement noise in the sensor.

    Nationell ämneskategori
    Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-121616 (URN)
    Tillgänglig från: 2015-09-28 Skapad: 2015-09-28 Senast uppdaterad: 2015-10-05Bibliografiskt granskad
    5. Greedy Reduction Algorithms for Mixtures of Exponential Family
    Öppna denna publikation i ny flik eller fönster >>Greedy Reduction Algorithms for Mixtures of Exponential Family
    2015 (Engelska)Ingår i: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 22, nr 6, s. 676-680Artikel i tidskrift (Refereegranskat) Published
    Abstract [en]

    In this letter, we propose a general framework for greedy reduction of mixture densities of exponential family. The performances of the generalized algorithms are illustrated both on an artificial example where randomly generated mixture densities are reduced and on a target tracking scenario where the reduction is carried out in the recursion of a Gaussian inverse Wishart probability hypothesis density (PHD) filter.

    Ort, förlag, år, upplaga, sidor
    Institute of Electrical and Electronics Engineers (IEEE), 2015
    Nyckelord
    Exponential family; extended target; integral square error; Kullback-Leibler divergence; mixture density; mixture reduction; target tracking
    Nationell ämneskategori
    Elektroteknik och elektronik
    Identifikatorer
    urn:nbn:se:liu:diva-112990 (URN)10.1109/LSP.2014.2367154 (DOI)000345236400005 ()
    Anmärkning

    Funding Agencies|Swedish research council (VR) under ETT [621-2010-4301]; SSF, project CUAS

    Tillgänglig från: 2015-01-12 Skapad: 2015-01-08 Senast uppdaterad: 2017-12-05
    6. Gaussian Mixture Reduction Using Reverse Kullback-Leibler Divergence
    Öppna denna publikation i ny flik eller fönster >>Gaussian Mixture Reduction Using Reverse Kullback-Leibler Divergence
    (Engelska)Manuskript (preprint) (Övrigt vetenskapligt)
    Nationell ämneskategori
    Signalbehandling
    Identifikatorer
    urn:nbn:se:liu:diva-121615 (URN)
    Tillgänglig från: 2015-09-28 Skapad: 2015-09-28 Senast uppdaterad: 2015-10-05
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