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What can regularization offer for estimation of dynamical systems?
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.ORCID iD: 0000-0001-8655-2655
2013 (English)In: 11th  IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP13, IFAC , 2013, 1-8 p.Conference paper, Published paper (Refereed)
Abstract [en]

Estimation of unknown dynamics is what system identication is about and acore problem in adaptive control and adaptive signal processing. It has long been known thatregularization can be quite benecial for general inverse problems of which system identicationis an example. But only recently, partly under the inuence of machine learning, the use ofwell tuned regularization for estimating linear dynamical systems has been investigated moreseriously. In this presentation we review these new results and discuss what they may mean forthe theory and practice of dynamical model estimation in general.

Place, publisher, year, edition, pages
IFAC , 2013. 1-8 p.
Keyword [en]
Identification methods design and analysis, Bayesian learning, Linear system identification
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-96766DOI: 10.3182/20130703-3-FR-4038.00155ISBN: 978-390282337-3 (print)OAI: oai:DiVA.org:liu-96766DiVA: diva2:643258
Conference
11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing (ALCOSP13), 3-5 July 2013, Caen, France
Available from: 2013-08-26 Created: 2013-08-26 Last updated: 2016-01-11Bibliographically approved

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Ljung, LennartChen, Tianshi

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CiteExportLink to record
Permanent link

Direct link
Cite
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
  • text
  • asciidoc
  • rtf