liu.seSök publikationer i DiVA
Ändra sökning
Avgränsa sökresultatet
1234567 1 - 50 av 4140
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Abara, Precious Ugo
    et al.
    Univ Padua, Italy; Tech Univ Munich, Germany.
    Ticozzi, Francesco
    Univ Padua, Italy; Dartmouth Coll, NH 03755 USA.
    Altafini, Claudio
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Spectral Conditions for Stability and Stabilization of Positive Equilibria for a Class of Nonlinear Cooperative Systems2018Ingår i: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 63, nr 2, s. 402-417Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Nonlinear cooperative systems associated to vector fields that are concave or subhomogeneous describe well interconnected dynamics that are of key interest for communication, biological, economical, and neural network applications. For this class of positive systems, we provide conditions that guarantee existence, uniqueness and stability of strictly positive equilibria. These conditions can be formulated directly in terms of the spectral radius of the Jacobian of the system. If control inputs are available, then it is shown how to use state feedback to stabilize an equilibrium point in the interior of the positive orthant.

    Ladda ner fulltext (pdf)
    fulltext
  • 2.
    Aberger, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Effects of Nonlinearities in Black Box Identification of an Industrial Robot2000Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This paper discusses effects of nonlinearities in black box identification of one axis of a robot. The used data come from a commercial ABB robot, IRB1400. A three-mass flexible model for the robot was built in MathModelica. The nonlinearities in the model are nonlinear friction and backlash in the gear box.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 3.
    Abrahamsson, Thomas
    et al.
    Saab Military Aircraft, Sweden.
    Andersson, Magnus
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    McKelvey, Tomas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Finite Element Model Updating Formulation Using Frequency Responses and Eigenfrequencies1996Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A novel frequency and modal domain formulation of the model updating problem is presented. Deviations in discrete frequency responses and eigenfrequencies, between the model to be updated and a reference model, constitute the criterion function. A successful updating thus results in a model with the reference's input-output relations at selected fre- quencies. The formulation is demonstrated to produce a criterion function with a global minimum having a large domain of attraction with respect to stiffness and mass variations. The method relies on mode grouping and uses a new extended modal assurance criterion number (eMAC) for identifying related modes. A quadratic objective with inexpensive evaluation of approximate Hessians give a rapid convergence to a minimum by the use of a regularized Gauss-Newton method. Physical bounds on parameters and complementary data, such as structural weight, are treated by imposing set constraints and linear equality constraints. Efficient function computation is obtained by model reduction using a moderately sized base of modes which is recomputed during the minimization. Statistical properties of updated parameters are discussed. A verification example show the performance of the method.

    Ladda ner fulltext (pdf)
    fulltext
    Ladda ner fulltext (ps)
    FULLTEXT01
  • 4.
    Abrahamsson, Tomas
    et al.
    Saab Military Aircraft, Sweden.
    McKelvey, Tomas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Study of some Approaches to Vibration Data Analysis1993Rapport (Övrigt vetenskapligt)
    Abstract [en]

    Using data from extensive vibrational tests of the new aircraft Saab 2000 three different methods for vibration analysis are studied. These methods are ERA (eigensystem realization algorithm), N4SID (a subspace method) and PEM (prediction error approach). We find that both the ERA and N4SID methods give good initial model parameter estimates that can be further improved by the use of PEM. We also find that all methods give good insights into the vibrational modes.

    Ladda ner fulltext (pdf)
    fulltext
    Ladda ner fulltext (ps)
    FULLTEXT01
  • 5.
    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)
    fulltext
  • 6.
    Adib Yaghmaie, Farnaz
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Gunnarsson, Svante
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    A New Result on Robust Adaptive Dynamic Programming for Uncertain Partially Linear Systems2019Ingår i: 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2019, s. 7480-7485Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we present a new result on robust adaptive dynamic programming for the Linear Quadratic Regulation (LQR) problem, where the linear system is subject to unmatched uncertainty. We assume that the states of the linear system are fully measurable and the matched uncertainty models unmeasurable states with an unspecified dimension. We use the small-gain theorem to give a sufficient condition such that the generated policies in each iteration of on-policy and off-policy routines guarantee robust stability of the overall uncertain system. The sufficient condition can be used to design the weighting matrices in the LQR problem. We use a simulation example to demonstrate the result.

  • 7.
    Adib Yaghmaie, Farnaz
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Gunnarsson, Svante
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Lewis, Frank L.
    Univ Texas Arlington, TX 76019 USA; Northeastern Univ, Peoples R China.
    Output regulation of unknown linear systems using average cost reinforcement learning2019Ingår i: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 110, artikel-id 108549Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this paper, we introduce an optimal average cost learning framework to solve output regulation problem for linear systems with unknown dynamics. Our optimal framework aims to design the controller to achieve output tracking and disturbance rejection while minimizing the average cost. We derive the Hamilton-Jacobi-Bellman (HJB) equation for the optimal average cost problem and develop a reinforcement algorithm to solve it. Our proposed algorithm is an off-policy routine which learns the optimal average cost solution completely model-free. We rigorously analyze the convergence of the proposed algorithm. Compared to previous approaches for optimal tracking controller design, we elevate the need for judicious selection of the discounting factor and the proposed algorithm can be implemented completely model-free. We support our theoretical results with a simulation example. (C) 2019 Elsevier Ltd. All rights reserved.

    Ladda ner fulltext (pdf)
    fulltext
  • 8.
    Adib Yaghmaie, Farnaz
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Using Reinforcement Learning for Model-free Linear Quadratic Control with Process and Measurement Noises2019Ingår i: 2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2019, s. 6510-6517Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we analyze a Linear Quadratic (LQ) control problem in terms of the average cost and the structure of the value function. We develop a completely model-free reinforcement learning algorithm to solve the LQ problem. Our algorithm is an off-policy routine where each policy is greedy with respect to all previous value functions. We prove that the algorithm produces stable policies given that the estimation errors remain small. Empirically, our algorithm outperforms the classical Q and off-policy learning routines.

  • 9.
    Adib Yaghmaie, Farnaz
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Linear Quadratic Control Using Model-Free Reinforcement Learning2023Ingår i: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 68, nr 2, s. 737-752Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this article, we consider linear quadratic (LQ) control problem with process and measurement noises. We analyze the LQ problem in terms of the average cost and the structure of the value function. We assume that the dynamics of the linear system is unknown and only noisy measurements of the state variable are available. Using noisy measurements of the state variable, we propose two model-free iterative algorithms to solve the LQ problem. The proposed algorithms are variants of policy iteration routine where the policy is greedy with respect to the average of all previous iterations. We rigorously analyze the properties of the proposed algorithms, including stability of the generated controllers and convergence. We analyze the effect of measurement noise on the performance of the proposed algorithms, the classical off-policy, and the classical Q-learning routines. We also investigate a model-building approach, inspired by adaptive control, where a model of the dynamical system is estimated and the optimal control problem is solved assuming that the estimated model is the true model. We use a benchmark to evaluate and compare our proposed algorithms with the classical off-policy, the classical Q-learning, and the policy gradient. We show that our model-building approach performs nearly identical to the analytical solution and our proposed policy iteration based algorithms outperform the classical off-policy and the classical Q-learning algorithms on this benchmark but do not outperform the model-building approach.

    Ladda ner fulltext (pdf)
    fulltext
  • 10.
    Adib Yaghmaie, Farnaz
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Modares, Hamidreza
    Michigan State University, USA.
    Online Optimal Tracking of Linear Systems with Adversarial Disturbances2023Ingår i: Transactions on Machine Learning Research, E-ISSN 2835-8856, nr 04Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a memory-augmented control solution to the optimal reference tracking problem for linear systems subject to adversarial disturbances. We assume that the dynamics of the linear system are known and that the reference signal is generated by a linear system with unknown dynamics. Under these assumptions, finding the optimal tracking controller is formalized as an online convex optimization problem that leverages memory of past disturbance and reference values to capture their temporal effects on the performance. That is, a (disturbance, reference)-action control policy is formalized, which selects the control actions as a linear map of the past disturbance and reference values. The online convex optimization is then formulated over the parameters of the policy on its past disturbance and reference values to optimize general convex costs. It is shown that our approach outperforms robust control methods and achieves a tight regret bound O(√T) where in our regret analysis, we have benchmarked against the best linear policy.

    Ladda ner fulltext (pdf)
    fulltext
  • 11.
    Adib Yaghmaie, Farnaz
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Nanyang Technol Univ, Singapore.
    Movric, Kristian Hengster
    Czech Tech Univ, Czech Republic.
    Lewis, Frank L.
    Univ Texas Arlington, TX 76019 USA; Northeastern Univ, Peoples R China.
    Su, Rong
    Nanyang Technol Univ, Singapore.
    Differential graphical games for H-infinity control of linear heterogeneous multiagent systems2019Ingår i: International Journal of Robust and Nonlinear Control, ISSN 1049-8923, E-ISSN 1099-1239, Vol. 29, nr 10, s. 2995-3013Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Differential graphical games have been introduced in the literature to solve state synchronization problem for linear homogeneous agents. When the agents are heterogeneous, the previous notion of graphical games cannot be used anymore and a new definition is required. In this paper, we define a novel concept of differential graphical games for linear heterogeneous agents subject to external unmodeled disturbances, which contain the previously introduced graphical game for homogeneous agents as a special case. Using our new formulation, we can solve both the output regulation and H-infinity output regulation problems. Our graphical game framework yields coupled Hamilton-Jacobi-Bellman equations, which are, in general, impossible to solve analytically. Therefore, we propose a new actor-critic algorithm to solve these coupled equations numerically in real time. Moreover, we find an explicit upper bound for the overall L2-gain of the output synchronization error with respect to disturbance. We demonstrate our developments by a simulation example.

    Ladda ner fulltext (pdf)
    fulltext
  • 12.
    Agebjär, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Model-Based Road Roughness Estimation2024Självständigt arbete på avancerad nivå (masterexamen), 28 hpStudentuppsats (Examensarbete)
    Abstract [en]

    Road roughness is the primary source of vehicle vibrations. This thesis investigates model-based methods for estimating road roughness in terms of the International Roughness Index (IRI) by measuring the chassis vibrations of the vehicle. This can provide NIRA Dynamics AB with a cost-effective pavement monitoring solution.

    Initially, system identification is performed on a physical car to estimate model parameters that reflect reality. Subsequently, two model-based IRI estimation methods are developed. One method relies on a transfer function between vertical chassis vibrations and the IRI according to a quarter-car model. The second method aims first to estimate the longitudinal road profile using a Kalman filter, and then calculate the IRI values from the estimated profile. This method can be implemented computationally efficiently and also offers the possibility of estimating the IRI using lateral vibrations. Both methods are validated using real-world data, and their performance is similar when using vertical vibrations, with the IRI estimation error’s standard deviation being roughly 10% to 20% of the reference value. However, the results are considerably worse when the estimation is purely based on lateral vibrations, indicating that lateral vibrations are not feasible for model-based IRI estimation, and the reasons for this are discussed.

    Ladda ner fulltext (pdf)
    fulltext
  • 13.
    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.

    Ladda ner fulltext (pdf)
    fulltext
  • 14.
    Ahlberg, Jörgen
    et al.
    Swedish Defence Research Agency, Sweden.
    Folkesson, Martin
    Swedish Defence Research Agency, Sweden.
    Grönwall, Christina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Horney, Tobias
    Swedish Defence Research Agency, Sweden.
    Jungert, Erland
    Swedish Defence Research Agency, Sweden.
    Klasén, Lena
    Swedish Defence Research Agency, Sweden.
    Ulvklo, Morgan
    Swedish Defence Research Agency, Sweden.
    Ground Target Recognition in a Query-Based Multi-Sensor Information System2006Rapport (Övrigt vetenskapligt)
    Abstract [en]

    We present a system covering the complete process for automatic ground target recognition, from sensor data to the user interface, i.e., from low level image processing to high level situation analysis. The system is based on a query language and a query processor, and includes target detection, target recognition, data fusion, presentation and situation analysis. This paper focuses on target recognition and its interaction with the query processor. The target recognitionis executed in sensor nodes, each containing a sensor and the corresponding signal/image processing algorithms. New sensors and algorithms are easily added to the system. The processing of sensor data is performed in two steps; attribute estimation and matching. First, several attributes, like orientation and dimensions, are estimated from the (unknown but detected) targets. These estimates are used to select the models of interest in a matching step, where the targetis matched with a number of target models. Several methods and sensor data types are used in both steps, and data is fused after each step. Experiments have been performed using sensor data from laser radar, thermal and visual cameras. Promising results are reported, demonstrating the capabilities of the target recognition algorithms, the advantages of the two-level data fusion and the query-based system.

    Ladda ner fulltext (pdf)
    fulltext
  • 15.
    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.
    A Distributed Second-Order Augmented Lagrangian Method for Distributed Model Predictive Control2021Ingår i: IFAC PAPERSONLINE, ELSEVIER , 2021, Vol. 54, nr 6, s. 192-199Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present a distributed second-order augmented Lagrangian method for distributed model predictive control. We distribute the computations for search direction, step size, and termination criteria over what is known as the clique tree of the problem and calculate each of them using message passing. The algorithm converges to its centralized counterpart and it requires fewer communications between sub-systems as compared to algorithms such as the alternating direction method of multipliers. Results from a simulation study confirm the efficiency of the framework. Copyright (C) 2021 The Authors.

  • 16.
    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.
    Parallel Exploitation for Tree-Structured Coupled Quadratic Programming in Julia2018Ingår i: Proceedings of the 22nd International Conference on System Theory, Control and Computing, IEEE, 2018, s. 597-602Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main idea in this paper is to implement a distributed primal-dual interior-point algorithm for loosely coupled Quadratic Programming problems. We implement this in Julia and show how can we exploit parallelism in order to increase the computational speed. We investigate the performance of the algorithm on a Model Predictive Control problem.

    Ladda ner fulltext (pdf)
    fulltext
  • 17.
    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.

  • 18.
    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 IoT, CA USA.
    Efficient Robust Model Predictive Control using Chordality2019Ingår i: 2019 18TH EUROPEAN CONTROL CONFERENCE (ECC), IEEE , 2019, s. 4270-4275Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we show that chordal structure can be used to devise efficient optimization methods for robust model predictive control problems. To this end, first the problem is converted to an equivalent robust quadratic programming formulation. We then illustrate how the chordal structure can be used to distribute the computations in a primal-dual interior-point method among computational agents, which in turn allows us to accelerate the algorithm by efficient parallel computations. We investigate performance of the framework in Julia using numerical examples.

    Ladda ner fulltext (pdf)
    fulltext
  • 19.
    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)
  • 20.
    Ahmadian, Amirhossein
    et al.
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Lindsten, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Enhancing Representation Learning with Deep Classifiers in Presence of Shortcut2023Ingår i: Proceedings of IEEE ICASSP 2023, 2023Konferensbidrag (Refereegranskat)
    Abstract [en]

    A deep neural classifier trained on an upstream task can be leveraged to boost the performance of another classifier in a related downstream task through the representations learned in hidden layers. However, presence of shortcuts (easy-to-learn features) in the upstream task can considerably impair the versatility of intermediate representations and, in turn, the downstream performance. In this paper, we propose a method to improve the representations learned by deep neural image classifiers in spite of a shortcut in upstream data. In our method, the upstream classification objective is augmented with a type of adversarial training where an auxiliary network, so called lens, fools the classifier by exploiting the shortcut in reconstructing images. Empirical comparisons in self-supervised and transfer learning problems with three shortcut-biased datasets suggest the advantages of our method in terms of downstream performance and/or training time.

  • 21.
    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.

  • 22.
    Aihara, ShinIchi
    et al.
    Tokyo University of Science, Japan.
    Bagch, Arunabha
    Twente University, Netherlands.
    Saha, Saikat
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Identification of Bates Stochastic Volatility Model by Using Non-Central Chi-Square Random Generation Method2012Ingår i: Proceedings of the 37th IEEE International Conference on Acoustics, Speech, and Signal Processing, 2012, , s. 4s. 3905-3908Konferensbidrag (Refereegranskat)
    Abstract [en]

    We study the 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 and its systems parameters is constructed. Simulation studies for checking the feasibility of the developed scheme are demonstrated.

    Ladda ner fulltext (pdf)
    ICASSP_ABS
  • 23.
    Aili, Adam
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Ekelund, Erik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Model-Based Design, Development and Control of an Underwater Vehicle2016Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [en]

    With the rising popularity of ROVs and other UV solutions, more robust and high performance controllers have become a necessity. A model of the ROV or UV can be a valuable tool during control synthesis. The main objective of this thesis was to use a model in design and development of controllers for an ROV.

    In this thesis, an ROV from Blue Robotics was used. The ROV was equipped with 6 thrusters placed such that the ROV was capable of moving in 6-DOFs. The ROV was further equipped with an IMU, two pressure sensors and a magnetometer. The ROV platform was further developed with EKF-based sensor fusion, a control system and manual control capabilities.

    To model the ROV, the framework of Fossen (2011) was used. The model was estimated using two different methods, the prediction-error method and an EKF-based method. Using the prediction-error method, it was found that the initial states of the quaternions had a large impact on the estimated parameters and the overall fit to validation data. A Kalman smoother was used to estimate the initial states. To circumvent the problems with the initial quaternions, an \abbrEKF was implemented to estimate the model parameters. The EKF estimator was less sensitive to deviations in the initial states and produced a better result than the prediction-error method. The resulting model was compared to validation data and described the angular velocities well with around 70 % fit.

    The estimated model was used to implement feedback linearisation which was used in conjunction with an attitude controller and an angular velocity controller. Furthermore, a depth controller was developed and tuned without the use of the model. Performance of the controllers was tested both in real tests and simulations. The angular velocity controller using feedback linearisation achieved good reference tracking. However, the attitude controller could not stabilise the system while using feedback linearisation. Both controllers' performance could be improved further by tuning the controllers' parameters during tests.

    The fact that the feedback linearisation made the ROV unstable, indicates that the attitude model is not good enough for use in feedback linearisation. To achieve stability, the magnitude of the parameters in the feedback linearisation were scaled down. The assumption that the ROV's center of rotation coincides with the placement of the ROV's center of gravity was presented as a possible source of error.

    In conclusion, good performance was achieved using the angular velocity controller. The ROV was easier to control with the angular velocity controller engaged compared to controlling it in open loop. More work is needed with the model to get acceptable performance from the attitude controller. Experiments to estimate the center of rotation and the center of gravity of the ROV may be helpful when further improving the model.

    Ladda ner fulltext (pdf)
    fulltext
  • 24.
    Akin, Bilal
    et al.
    Texas Instruments Inc, USA.
    Choi, Seungdeog
    Texas A&M University, USA.
    Orguner, Umut
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Toliyat, Hamid A
    Texas A&M University, USA.
    A Simple Real-Time Fault Signature Monitoring Tool for Motor-Drive-Embedded Fault Diagnosis Systems2011Ingår i: IEEE Transactions on Industrial Electronics, ISSN 0278-0046, E-ISSN 1557-9948, Vol. 58, nr 5, s. 1990-2001Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The reference frame theory constitutes an essential aspect of electric machine analysis and control. In this study, apart from the conventional applications, it is reported that the reference frame theory approach can successfully be applied to real-time fault diagnosis of electric machinery systems as a powerful toolbox to find the magnitude and phase quantities of fault signatures with good precision as well. The basic idea is to convert the associated fault signature to a dc quantity, followed by the computation of the signals average in the fault reference frame to filter out the rest of the signal harmonics, i.e., its ac components. As a natural consequence of this, neither a notch filter nor a low-pass filter is required to eliminate fundamental component or noise content. Since the incipient fault mechanisms have been studied for a long time, the motor fault signature frequencies and fault models are very well-known. Therefore, ignoring all other components, the proposed method focuses only on certain fault signatures in the current spectrum depending on the examined motor fault. Broken rotor bar and eccentricity faults are experimentally tested online using a TMS320F2812 digital signal processor (DSP) to prove the effectiveness of the proposed method. In this application, only the readily available drive hardware is used without employing additional components such as analog filters, signal conditioning board, external sensors, etc. As the motor drive processing unit, the DSP is utilized both for motor control and fault detection purposes, providing instantaneous fault information. The proposed algorithm processes the measured data in real time to avoid buffering and large-size memory needed in order to enhance the practicability of this method. Due to the short-time convergence capability of the algorithm, the fault status is updated in each second. The immunity of the algorithm against non-ideal cases such as measurement offset errors and phase unbalance is theoretically and experimentally verified. Being a model-independent fault analyzer, this method can be applied to all multiphase and single-phase motors.

  • 25.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1993Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the lest-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 26.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1994Ingår i: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 2, s. 85-90Konferensbidrag (Refereegranskat)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the lest-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 27.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1994Rapport (Övrigt vetenskapligt)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the least-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 28.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    The Least-Squares Identification of FIR Systems Subject to Worst-Case Noise1994Ingår i: Systems & control letters (Print), ISSN 0167-6911, E-ISSN 1872-7956, Vol. 23, nr 5, s. 329-338Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The least-squares identification of FIR systems is analyzed assuming that the noise is a bounded signal and the input signal is a pseudo-random binary sequence. A lower bound on the worst-case transfer function error shows that the least-square estimate of the transfer function diverges as the order of the FIR system is increased. This implies that, in the presence of the worst-case noise, the trade-off between the estimation error due to the disturbance and the bias error (due to unmodeled dynamics) is significantly different from the corresponding trade-off in the random error case: with a worst-case formulation, the model complexity should not increase indefinitely as the size of the data set increases.

  • 29.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On the Choice of Norms in System Identification1994Ingår i: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 2, s. 103-108Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 30.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On the Choice of Norms in System Identification1994Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 31.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On the Choice of Norms in System Identification1996Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 32.
    Akçay, Hüseyin
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Hjalmarsson, Håkan
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    On the Choice of Norms in System Identification1994Rapport (Övrigt vetenskapligt)
    Abstract [en]

    In this paper we discuss smooth and sensitive norms for prediction error system identification when the disturbances are magnitude bounded. Formal conditions for sensitive norms, which give an order of magnitude faster convergence of the parameter estimate variance, are developed. However, it also is shown that the parameter estimate variance convergence rate of sensitive norms is arbitrarily bad for certain distributions. A necessary condition for a norm to be statistically robust with respect to the family F(C) of distributions with support [-C, C] for some arbitrary C>0 is that its second derivative does not vanish on the support. A direct consequence of this observation is that the quadratic norm is statistically robust among all lp-norms, p⩽2<∞ for F(C).

  • 33.
    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
  • 34.
    Ala, Tirdad Seifi
    et al.
    Oticon AS, Denmark; Univ Nottingham, Scotland.
    Graversen, Carina
    Oticon AS, Denmark.
    Wendt, Dorothea
    Oticon AS, Denmark; Tech Univ Denmark, Denmark.
    Alickovic, Emina
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Oticon AS, Denmark.
    Whitmer, William M.
    Univ Nottingham, Scotland.
    Lunner, Thomas
    Oticon AS, Denmark.
    An exploratory Study of EEG Alpha Oscillation and Pupil Dilation in Hearing-Aid Users During Effortful listening to Continuous Speech2020Ingår i: PLOS ONE, E-ISSN 1932-6203, Vol. 15, nr 7, artikel-id e0235782Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Individuals with hearing loss allocate cognitive resources to comprehend noisy speech in everyday life scenarios. Such a scenario could be when they are exposed to ongoing speech and need to sustain their attention for a rather long period of time, which requires listening effort. Two well-established physiological methods that have been found to be sensitive to identify changes in listening effort are pupillometry and electroencephalography (EEG). However, these measurements have been used mainly for momentary, evoked or episodic effort. The aim of this study was to investigate how sustained effort manifests in pupillometry and EEG, using continuous speech with varying signal-to-noise ratio (SNR). Eight hearing-aid users participated in this exploratory study and performed a continuous speech-in-noise task. The speech material consisted of 30-second continuous streams that were presented from loudspeakers to the right and left side of the listener (+/- 30 degrees azimuth) in the presence of 4-talker background noise (+180 degrees azimuth). The participants were instructed to attend either to the right or left speaker and ignore the other in a randomized order with two different SNR conditions: 0 dB and -5 dB (the difference between the target and the competing talker). The effects of SNR on listening effort were explored objectively using pupillometry and EEG. The results showed larger mean pupil dilation and decreased EEG alpha power in the parietal lobe during the more effortful condition. This study demonstrates that both measures are sensitive to changes in SNR during continuous speech.

    Ladda ner fulltext (pdf)
    fulltext
  • 35.
    Alami, Mohsen
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    Interval Based Parameter Identification for System Biology2012Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Det här examensarbetet studerar problemet med parameteridentifiering för systembiologi. Två metoder har studerats. Metoden med intervallanalys använder union av intervallvektorer som klass av objekt för att manipulera och bilda inre och yttre approximationer av kompakta mängder. Denna metod fungerar väl för modeller givna som ett system av differentialekvationer, men har sina begränsningar, eftersom det analytiska uttrycket för lösningen till differentialekvationen som är nödvändigt att känna till för att kunna formulera inkluderande funktioner, inte alltid är tillgängliga. Den andra studerade metoden, använder SDP-relaxering, som ett sätt att komma runt problemet med olinjäritet och icke-konvexitet i systemet. Denna metod, implementerad i toolboxen bio.SDP, utgår från system av differensekvationer, framtagna via Eulers diskretiserings metod. Diskretiseringsmetoden innehåller fel och osäkerhet, vilket gör det nödvändigt att estimera en gräns för felets storlek. Några felestimeringsmetoder har studerats. Metoden med ∞-norm optimering, också kallat worst-case-∞-norm är tillämpat på ett-stegs felestimerings metoder.

    Metoderna har illustrerats genom att lösa två system biologiska problem och de accepterade parametermängderna, benämnt SCP, har jämförts och diskuterats.

    Ladda ner fulltext (pdf)
    fulltext
  • 36.
    Albertos, Pedro
    et al.
    Polytechnical University of Valencia, Spain.
    Goodwin, Graham C.
    University of Newcastle, Australia.
    Isaksson, Alf
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
    A Pseudo Linear Regression Algorithm for On-Line Parameter Estimation with Missing Data1992Rapport (Övrigt vetenskapligt)
  • 37.
    Algethami, Abdullah
    et al.
    Taif Univ, Saudi Arabia.
    Sarkar, Rajasree
    Indian Inst Technol Delhi, India.
    Amrr, Syed
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Banerjee, Arunava
    Univ Alberta, Canada.
    Bio-mimetic Autonomous Underwater Vehicle Control Using Time Delayed Estimation Technique2023Ingår i: 2023 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, AIM, IEEE , 2023, s. 930-935Konferensbidrag (Refereegranskat)
    Abstract [en]

    An autonomous underwater vehicle (AUV) is a crewless robotic vehicle that dives into the water and performs without human assistance. This paper focuses on developing trajectory tracking control for bio-mimetic AUV system under uncertain environments. Therefore, a relatively new control technique called time delay-based estimation control is proposed for trajectory tracking under multiple uncertainties. This algorithm estimates the total disturbance in the system using immediate past information of input and output of feedback state and control variables. The benefit of this scheme is that it avoids assumptions about a priori upper bound information of disturbance. Further, the control structure is simple and does not require any high-frequency switching or high gain to nullify the effects of disturbance. The theoretical analysis of the proposed scheme guarantees the uniformly ultimate bounded stability of the closed-loop system. The numerical analysis is also carried out to validate the control performance of the given algorithm for lemniscate reference path tracking.

  • 38.
    Ali Abdul-Amir, Ahmed
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik.
    Att lösa reglertekniska problem med Modelica2008Självständigt arbete på avancerad nivå (magisterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Objektorienterad modellering är ett utmärkt sätt att analysera och modellera fysikaliska system. Den ger möjlighet att hantera stora, komplexa och blandade system.

    Modelica är ett exempel på ett multidomän modelleringsspråk som är ekvationsbaserat och hanterar modeller från olika fysikaliska domäner. Det är baserat på principer från objektorientering och hanterar icke-kausala problem. Modelicas struktur gör att befintliga modeller kan delas upp i delmodeller som kan designas och testas oberoende av de andra delmodellerna. Det ger överskådlig bild av fysikaliska systemet. Modellbibliotek i Modelica kan enkelt modifieras för att designa nya komponenter.

    Modellering av fysikaliska system, speciellt mekaniska eller mekatroniska system ger upphov till DAE system med index 2 eller 3. Det resulterar svårigheter vid simulering av modeller. En automatiserad symbolisk manipulering av DAE systemen behövs för att underlätta simuleringen.

    För att simulera modeller skrivna i Modelica, behövs en kompilator och ett simuleringsverktyg. Dymola är det dominerande verktyget för dessa ändamål. Man har tillgång till Modelicas standardbibliotek via ett grafiskt gränssnitt. Vid simulering kontrolleras modellen så att Modelicas syntax är uppfylld. Sedan kompileras och simuleras modellen.

    Ladda ner fulltext (pdf)
    FULLTEXT01
  • 39.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Eriksholm Res Ctr, Denmark.
    Dorszewski, Tobias
    Eriksholm Res Ctr, Denmark; Univ Stuttgart, Germany.
    Christiansen, Thomas U.
    Oticon AS, Denmark.
    Eskelund, Kasper
    Oticon AS, Denmark.
    Gizzi, Leonardo
    Univ Stuttgart, Germany.
    Skoglund, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Eriksholm Res Ctr, Denmark.
    Wendt, Dorothea
    Eriksholm Res Ctr, Denmark; Tech Univ Denmark, Denmark.
    Predicting EEG Responses to Attended Speech via Deep Neural Networks for Speech2023Ingår i: 2023 45TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY, EMBC, IEEE , 2023Konferensbidrag (Refereegranskat)
    Abstract [en]

    Attending to the speech stream of interest in multi-talker environments can be a challenging task, particularly for listeners with hearing impairment. Research suggests that neural responses assessed with electroencephalography (EEG) are modulated by listener's auditory attention, revealing selective neural tracking (NT) of the attended speech. NT methods mostly rely on hand-engineered acoustic and linguistic speech features to predict the neural response. Only recently, deep neural network (DNN) models without specific linguistic information have been used to extract speech features for NT, demonstrating that speech features in hierarchical DNN layers can predict neural responses throughout the auditory pathway. In this study, we go one step further to investigate the suitability of similar DNN models for speech to predict neural responses to competing speech observed in EEG. We recorded EEG data using a 64-channel acquisition system from 17 listeners with normal hearing instructed to attend to one of two competing talkers. Our data revealed that EEG responses are significantly better predicted by DNN-extracted speech features than by hand-engineered acoustic features. Furthermore, analysis of hierarchical DNN layers showed that early layers yielded the highest predictions. Moreover, we found a significant increase in auditory attention classification accuracies with the use of DNN-extracted speech features over the use of hand-engineered acoustic features. These findings open a new avenue for development of new NT measures to evaluate and further advance hearing technology.

  • 40.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Kevric, Jasmin
    Int Burch University, Bosnia and Herceg.
    Subasi, Abdulhamit
    Effat University, Saudi Arabia.
    Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction2018Ingår i: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 39, s. 94-102Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This study proposes a new model which is fully specified for automated seizure onset detection and seizure onset prediction based on electroencephalography (EEG) measurements. We processed two archetypal EEG databases, Freiburg (intracranial EEG) and CHB-MIT (scalp EEG), to find if our model could outperform the state-of-the art models. Four key components define our model: (1) multiscale principal component analysis for EEG de-noising, (2) EEG signal decomposition using either empirical mode decomposition, discrete wavelet transform or wavelet packet decomposition, (3) statistical measures to extract relevant features, (4) machine learning algorithms. Our model achieved overall accuracy of 100% in ictal vs. inter-ictal EEG for both databases. In seizure onset prediction, it could discriminate between inter-ictal, pre-ictal, and ictal EEG with the accuracy of 99.77%, and between inter-ictal and pre-ictal EEG states with the accuracy of 99.70%. The proposed model is general and should prove applicable to other classification tasks including detection and prediction regarding bio-signals such as EMG and ECG. (C) 2017 Elsevier Ltd. All rights reserved.

  • 41.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Lunner, Thomas
    Linköpings universitet, Institutet för handikappvetenskap (IHV). Linköpings universitet, Institutionen för klinisk och experimentell medicin, Avdelningen för neuro- och inflammationsvetenskap. Linköpings universitet, Medicinska fakulteten. Eriksholm Research Centre, Oticon A/S, 20 Rortangvej, Snekkersten, Denmark.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    A System Identification Approach to Determining Listening Attention from EEG Signals2016Ingår i: 2016 24TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO), IEEE , 2016, s. 31-35Konferensbidrag (Refereegranskat)
    Abstract [en]

    We still have very little knowledge about how ourbrains decouple different sound sources, which is known assolving the cocktail party problem. Several approaches; includingERP, time-frequency analysis and, more recently, regression andstimulus reconstruction approaches; have been suggested forsolving this problem. In this work, we study the problem ofcorrelating of EEG signals to different sets of sound sources withthe goal of identifying the single source to which the listener isattending. Here, we propose a method for finding the number ofparameters needed in a regression model to avoid overlearning,which is necessary for determining the attended sound sourcewith high confidence in order to solve the cocktail party problem.

    Ladda ner fulltext (pdf)
    fulltext
  • 42.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Oticon AS, Denmark.
    Lunner, Thomas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutet för handikappvetenskap (IHV). Oticon AS, Denmark; Tech Univ Denmark, Denmark.
    Gustafsson, Fredrik
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    A Tutorial on Auditory Attention Identification Methods2019Ingår i: Frontiers in Neuroscience, ISSN 1662-4548, E-ISSN 1662-453X, Vol. 13, artikel-id 153Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Auditory attention identification methods attempt to identify the sound source of a listeners interest by analyzing measurements of electrophysiological data. We present a tutorial on the numerous techniques that have been developed in recent decades, and we present an overview of current trends in multivariate correlation-based and model-based learning frameworks. The focus is on the use of linear relations between electrophysiological and audio data. The way in which these relations are computed differs. For example, canonical correlation analysis (CCA) finds a linear subset of electrophysiological data that best correlates to audio data and a similar subset of audio data that best correlates to electrophysiological data. Model-based (encoding and decoding) approaches focus on either of these two sets. We investigate the similarities and differences between these linear model philosophies. We focus on (1) correlation-based approaches (CCA), (2) encoding/decoding models based on dense estimation, and (3) (adaptive) encoding/decoding models based on sparse estimation. The specific focus is on sparsity-driven adaptive encoding models and comparing the methodology in state-of-the-art models found in the auditory literature. Furthermore, we outline the main signal processing pipeline for how to identify the attended sound source in a cocktail party environment from the raw electrophysiological data with all the necessary steps, complemented with the necessary MATLAB code and the relevant references for each step. Our main aim is to compare the methodology of the available methods, and provide numerical illustrations to some of them to get a feeling for their potential. A thorough performance comparison is outside the scope of this tutorial.

    Ladda ner fulltext (pdf)
    fulltext
  • 43.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Oticon AS, Denmark.
    Lunner, Thomas
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Institutet för handikappvetenskap (IHV). Tech Univ Denmark, Denmark.
    Wendt, Dorothea
    Tech Univ Denmark, Denmark.
    Fiedler, Lorenz
    Oticon AS, Denmark.
    Hietkamp, Renskje
    Oticon AS, Denmark.
    Ng, Hoi Ning Elaine
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten. Linköpings universitet, Institutet för handikappvetenskap (IHV). Oticon AS, Denmark.
    Graversen, Carina
    Oticon AS, Denmark.
    Neural Representation Enhanced for Speech and Reduced for Background Noise With a Hearing Aid Noise Reduction Scheme During a Selective Attention Task2020Ingår i: Frontiers in Neuroscience, ISSN 1662-4548, E-ISSN 1662-453X, Vol. 14, artikel-id 846Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objectives Selectively attending to a target talker while ignoring multiple interferers (competing talkers and background noise) is more difficult for hearing-impaired (HI) individuals compared to normal-hearing (NH) listeners. Such tasks also become more difficult as background noise levels increase. To overcome these difficulties, hearing aids (HAs) offer noise reduction (NR) schemes. The objective of this study was to investigate the effect of NR processing (inactive, where the NR feature was switched off,vs.active, where the NR feature was switched on) on the neural representation of speech envelopes across two different background noise levels [+3 dB signal-to-noise ratio (SNR) and +8 dB SNR] by using a stimulus reconstruction (SR) method. Design To explore how NR processing supports the listeners selective auditory attention, we recruited 22 HI participants fitted with HAs. To investigate the interplay between NR schemes, background noise, and neural representation of the speech envelopes, we used electroencephalography (EEG). The participants were instructed to listen to a target talker in front while ignoring a competing talker in front in the presence of multi-talker background babble noise. Results The results show that the neural representation of the attended speech envelope was enhanced by the active NR scheme for both background noise levels. The neural representation of the attended speech envelope at lower (+3 dB) SNR was shifted, approximately by 5 dB, toward the higher (+8 dB) SNR when the NR scheme was turned on. The neural representation of the ignored speech envelope was modulated by the NR scheme and was mostly enhanced in the conditions with more background noise. The neural representation of the background noise was modulated (i.e., reduced) by the NR scheme and was significantly reduced in the conditions with more background noise. The neural representation of the net sum of the ignored acoustic scene (ignored talker and background babble) was not modulated by the NR scheme but was significantly reduced in the conditions with a reduced level of background noise. Taken together, we showed that the active NR scheme enhanced the neural representation of both the attended and the ignored speakers and reduced the neural representation of background noise, while the net sum of the ignored acoustic scene was not enhanced. Conclusion Altogether our results support the hypothesis that the NR schemes in HAs serve to enhance the neural representation of speech and reduce the neural representation of background noise during a selective attention task. We contend that these results provide a neural index that could be useful for assessing the effects of HAs on auditory and cognitive processing in HI populations.

    Ladda ner fulltext (pdf)
    fulltext
  • 44.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Eriksholm Res Ctr, Denmark.
    Mendoza, Carlos Francisco
    Eriksholm Res Ctr, Denmark; Lund Univ, Sweden.
    Segar, Andrew
    Eriksholm Res Ctr, Denmark; Lund Univ, Sweden.
    Sandsten, Maria
    Lund Univ, Sweden.
    Skoglund, Martin
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Eriksholm Res Ctr, Denmark.
    DECODING AUDITORY ATTENTION FROM EEG DATA USING CEPSTRAL ANALYSIS2023Ingår i: 2023 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW, IEEE , 2023, artikel-id 6844Konferensbidrag (Refereegranskat)
    Abstract [en]

    Recent studies of selective auditory attention have demonstrated that neural responses recorded with electroencephalogram (EEG) can be decoded to classify the attended talker in everyday multitalker cocktail-party environments. This is generally referred to as the auditory attention decoding (AAD) and could lead to a breakthrough for the next-generation of hearing aids (HAs) to have the ability to be cognitively controlled. The aim of this paper is to investigate whether cepstral analysis can be used as a more robust mapping between speech and EEG. Our preliminary analysis revealed an average AAD accuracy of 96%. Moreover, we observed a significant increase in auditory attention classification accuracies with our approach over the use of traditional AAD methods (7% absolute increase). Overall, our exploratory study could open a new avenue for developing new AAD methods to further advance hearing technology. We recognize that additional research is needed to elucidate the full potential of cepstral analysis for AAD.

  • 45.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten. Oticon AS, Denmark.
    Ng, Hoi Ning, Elaine
    Linköpings universitet, Institutionen för beteendevetenskap och lärande, Handikappvetenskap. Linköpings universitet, Filosofiska fakulteten. Linköpings universitet, Institutet för handikappvetenskap (IHV). Oticon AS, Denmark.
    Fiedler, Lorenz
    Oticon AS, Denmark.
    Santurette, Sebastien
    Oticon AS, Denmark; Tech Univ Denmark, Denmark.
    Innes-Brown, Hamish
    Oticon AS, Denmark.
    Graversen, Carina
    Oticon AS, Denmark.
    Effects of Hearing Aid Noise Reduction on Early and Late Cortical Representations of Competing Talkers in Noise2021Ingår i: Frontiers in Neuroscience, ISSN 1662-4548, E-ISSN 1662-453X, Vol. 15, artikel-id 636060Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objectives Previous research using non-invasive (magnetoencephalography, MEG) and invasive (electrocorticography, ECoG) neural recordings has demonstrated the progressive and hierarchical representation and processing of complex multi-talker auditory scenes in the auditory cortex. Early responses (&lt;85 ms) in primary-like areas appear to represent the individual talkers with almost equal fidelity and are independent of attention in normal-hearing (NH) listeners. However, late responses (&gt;85 ms) in higher-order non-primary areas selectively represent the attended talker with significantly higher fidelity than unattended talkers in NH and hearing-impaired (HI) listeners. Motivated by these findings, the objective of this study was to investigate the effect of a noise reduction scheme (NR) in a commercial hearing aid (HA) on the representation of complex multi-talker auditory scenes in distinct hierarchical stages of the auditory cortex by using high-density electroencephalography (EEG). Design We addressed this issue by investigating early (&lt;85 ms) and late (&gt;85 ms) EEG responses recorded in 34 HI subjects fitted with HAs. The HA noise reduction (NR) was either on or off while the participants listened to a complex auditory scene. Participants were instructed to attend to one of two simultaneous talkers in the foreground while multi-talker babble noise played in the background (+3 dB SNR). After each trial, a two-choice question about the content of the attended speech was presented. Results Using a stimulus reconstruction approach, our results suggest that the attention-related enhancement of neural representations of target and masker talkers located in the foreground, as well as suppression of the background noise in distinct hierarchical stages is significantly affected by the NR scheme. We found that the NR scheme contributed to the enhancement of the foreground and of the entire acoustic scene in the early responses, and that this enhancement was driven by better representation of the target speech. We found that the target talker in HI listeners was selectively represented in late responses. We found that use of the NR scheme resulted in enhanced representations of the target and masker speech in the foreground and a suppressed representation of the noise in the background in late responses. We found a significant effect of EEG time window on the strengths of the cortical representation of the target and masker. Conclusion Together, our analyses of the early and late responses obtained from HI listeners support the existing view of hierarchical processing in the auditory cortex. Our findings demonstrate the benefits of a NR scheme on the representation of complex multi-talker auditory scenes in different areas of the auditory cortex in HI listeners.

    Ladda ner fulltext (pdf)
    fulltext
  • 46.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Subasi, Abdulhamit
    Effat Univ, Saudi Arabia.
    Automatic Detection of Alzheimer Disease Based on Histogram and Random Forest2020Ingår i: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING, CMBEBIH 2019, SPRINGER , 2020, Vol. 73, s. 91-96Konferensbidrag (Refereegranskat)
    Abstract [en]

    Alzheimer disease is one of the most prevalent dementia types affecting elder population. On-time detection of the Alzheimer disease (AD) is valuable for finding new approaches for the AD treatment. Our primary interest lies in obtaining a reliable, but simple and fast model for automatic AD detection. The approach we introduced in the present contribution to identify AD is based on the application of machine learning (ML) techniques. For the first step, we use histogram to transform brain images to feature vectors, containing the relevant "brain" features, which will later serve as the inputs in the classification step. Next, we use the ML algorithms in the classification task to identify AD. The model presented and elaborated in the present contribution demonstrated satisfactory performances. Experimental results suggested that the Random Forest classifier can discriminate the AD subjects from the control subjects. The presented modeling approach, consisting of the histogram as the feature extractor and Random Forest as the classifier, yielded to the sufficiently high overall accuracy rate of 85.77%.

  • 47.
    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
  • 48.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Subasi, Abdulhamit
    Effat University, Saudi Arabia.
    Medical Decision Support System for Diagnosis of Heart Arrhythmia using DWT and Random Forests Classifier2016Ingår i: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 40, nr 4, s. 108-Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of different statistical features were extracted from the obtained frequency bands to denote the distribution of wavelet coefficients. This study shows that RF classifier achieves superior performances compared to other decision tree methods using 10-fold cross-validation for the ECG datasets and the obtained results suggest that further significant improvements in terms of classification accuracy can be accomplished by the proposed classification system. Accurate ECG signal classification is the major requirement for detection of all arrhythmia types. Performances of the proposed system have been evaluated on two different databases, namely MIT-BIH database and St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database. For MIT-BIH database, RF classifier yielded an overall accuracy 99.33 % against 98.44 and 98.67 % for the C4.5 and CART classifiers, respectively. For St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database, RF classifier yielded an overall accuracy 99.95 % against 99.80 % for both C4.5 and CART classifiers, respectively. The combined model with multiscale principal component analysis (MSPCA) de-noising, discrete wavelet transform (DWT) and RF classifier also achieves better performance with the area under the receiver operating characteristic (ROC) curve (AUC) and F- measure equal to 0.999 and 0.993 for MIT-BIH database and 1 and 0.999 for and St. Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database, respectively. Obtained results demonstrate that the proposed system has capacity for reliable classification of ECG signals, and to assist the clinicians for making an accurate diagnosis of cardiovascular disorders (CVDs).

  • 49.
    Alickovic, Emina
    et al.
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    Subasi, Abdulhamit
    Effat Univ, Saudi Arabia.
    Normalized Neural Networks for Breast Cancer Classification2020Ingår i: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING, CMBEBIH 2019, SPRINGER , 2020, Vol. 73, s. 519-524Konferensbidrag (Refereegranskat)
    Abstract [en]

    In almost all parts of the world, breast cancer is one of the major causes of death among women. But at the same time, it is one of the most curable cancers if it is diagnosed at early stage. This paper tries to find a model that diagnose and classify breast cancer with high accuracy and help to both patients and doctors in the future. Here we develop a model using Normalized Multi Layer Perceptron Neural Network to classify breast cancer with high accuracy. The results achieved is very good (accuracy is 99.27%). It is very promising result compared to previous researches where Artificial Neural Networks were used. As benchmark test, Breast Cancer Wisconsin (Original) was used.

  • 50.
    Aljanaideh, Khaled F.
    et al.
    MathWorks, MA 01760 USA.
    Bhattacharjee, Debraj
    MathWorks, MA 01760 USA.
    Singh, Rajiv
    MathWorks, MA 01760 USA.
    Ljung, Lennart
    Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska fakulteten.
    New Features in the System Identification Toolbox - Rapprochements with Machine Learning2021Ingår i: IFAC PAPERSONLINE, ELSEVIER , 2021, Vol. 54, nr 7, s. 369-373Konferensbidrag (Refereegranskat)
    Abstract [en]

    The R2021b release of the System Identification ToolboxTM for MATLAB contains new features that enable the use of machine learning techniques for nonlinear system identification. With this release it is possible to build nonlinear ARX models with regression tree ensemble and Gaussian process regression mapping functions. The release contains several other enhancements including, but not limited to, (a) online state estimation using the extended Kalman filter and the unscented Kalman filter with code generation capability; (b) improved handling of initial conditions for transfer functions and polynomial models; (c) a new architecture of nonlinear black-box models that streamlines regressor handling, reduces memory footprint and improves numerical accuracy; and (d) easy incorporation of identification apps in teaching tools and interactive examples by leveraging the Live Editor tasks of MATLAB. Copyright (C) 2021 The Authors.

1234567 1 - 50 av 4140
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf