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A Semiparametric Bayesian Approach to Wiener System Identification
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.
University of California, Berkeley, USA.
2011 (English)Report (Other academic)
Abstract [en]

We consider a semiparametric, i.e. a mixed parametric/nonparametric, model of a Wiener system. We use a state-space model for the linear dynamical system and a nonparametric Gaussian process (GP) model for the static nonlinearity. The GP model is a flexible model that can describe different types of nonlinearities while avoiding making strong assumptions such as monotonicity. We derive an inferential method based on recent advances in Monte Carlo statistical methods, known as Particle Markov Chain Monte Carlo (PMCMC). The idea underlying PMCMC is to use a particle filter (PF) to generate a sample state trajectory in a Markov chain Monte Carlo sampler. We use a recently proposed PMCMC sampler, denoted particle Gibbs with backward simulation, which has been shown to be efficient even when we use very few particles in the PF. The resulting method is used in a simulation study to identify two different Wiener systems with non-invertible nonlinearities.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2011. , 8 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 3037
Keyword [en]
Wiener system identification, particle Markov chain Monte Carlo, Gibbs sampling, Bayesian methods, Gaussian processes
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-97976ISRN: LiTH-ISY-R-3037OAI: oai:DiVA.org:liu-97976DiVA: diva2:650874
Projects
CADICSCNDM
Funder
Swedish Research Council
Available from: 2013-09-23 Created: 2013-09-23 Last updated: 2014-09-01Bibliographically approved

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Lindsten, FredrikSchön, Thomas

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CiteExportLink to record
Permanent link

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