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L2 Model Reduction and Variance Reduction
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.
2007 (English)Report (Other academic)
Abstract [en]

In this contribution we examine certain variance properties of model reduction. The focus is on L2 model reduction, but some general results are also presented. These general results can be used to analyze various other model reduction schemes. The models we study are finite impulse response (FIR) and output error (OE) models. We compare the variance of two estimated models. The first one is estimated directly from data and the other one is computed by reducing a high order model, by L2 model reduction. In the FIR case we show that it is never better to estimate the model directly from data, compared to estimating it via L2 model reduction of a high order FIR model. For OE models we show that the reduced model has the same variance as the directly estimated one if the reduced model class used contains the true system.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2007. , 17 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2801
Keyword [en]
identication, model reduction, variance reduction
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55834ISRN: LiTH-ISY-R-2801OAI: oai:DiVA.org:liu-55834DiVA: diva2:316704
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-10-02Bibliographically approved

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Ljung, Lennart

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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