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Frequency-Domain Identification of Continuous-Time ARMA Models from Non-Uniformly Sampled Data
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2005 (English)Report (Other academic)
Abstract [en]

This paper treats direct identification of continuous-time autoregressive moving average (CARMA) time-series models. The main result is a method for estimating the continuous-time power spectral density fromnon-uniformly sampled data. It is based on the interpolation (smoothing) using the Kalman filter. A deeper analysis is also carried out for the case of uniformly sampled data. This analysis provides a basis for proceeding with the non-uniform case. Numerical examples illustrating the performance of the method are also provided both, for spectral and subsequent parameter estimation.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2005. , 12 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2693
Keyword [en]
Continuous-time systems, Parameter estimation, Continuous-time ARMA, CARMA, Continuous-time noise model, Whittle likelihood estimation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56027ISRN: LiTH-ISY-R-2693OAI: oai:DiVA.org:liu-56027DiVA: diva2:316917
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-06-19Bibliographically approved

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Gillberg, JonasLjung, Lennart

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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