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Bayesian kernel-based system identification with quantized output data
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-9368-3079
2015 (English)In: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 48, no 28, 455-460 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we introduce a novel method for linear system identification with quantized output data. We model the impulse response as a zero-mean Gaussian process whose covariance (kernel) is given by the recently proposed stable spline kernel, which encodes information on regularity and exponential stability. This serves as a starting point to cast our system identification problem into a Bayesian framework. We employ Markov Chain Monte Carlo (MCMC) methods to provide an estimate of the system. In particular, we show how to design a Gibbs sampler which quickly converges to the target distribution. Numerical simulations show a substantial improvement in the accuracy of the estimates over state-of-the-art kernel-based methods when employed in identification of systems with quantized data.

Place, publisher, year, edition, pages
Elsevier, 2015. Vol. 48, no 28, 455-460 p.
Keyword [en]
Impulse response, Linear systems, Markov processes, Numerical methods, Religious buildings, Bayesian frameworks, Gibbs samplers, Identification of systems, Kernel based methods, Markov chain Monte Carlo method, State of the art, System identification problems, Zero mean Gaussian process, Monte Carlo methods
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-195439DOI: 10.1016/j.ifacol.2015.12.170ScopusID: 2-s2.0-84988452886OAI: oai:DiVA.org:kth-195439DiVA: diva2:1046628
Note

QC 20161114

Available from: 2016-11-14 Created: 2016-11-03 Last updated: 2016-11-14Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
  • vancouver
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More styles
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  • nn-NB
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Output format
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  • asciidoc
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