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Model Reduction of Estimated Models
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1988 (English)Report (Other academic)
Abstract [en]

This paper deals with the connection between system identification and model reduction. We will from a statistical point of view discuss how to reduce the order of high-order models obtained from an identification experiment. We will apply these results to estimate transfer functions by means of a high-order FIR model and model reduction. The model reduction techniques considered are: Frequency weighted L2-norm model reduction and model reduction via a truncated frequency weighted balanced realization.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1988. , 6 p.
Series
LiTH-ISY-I, ISSN 8765-4321 ; 906
Keyword [en]
Mathematical statistics, Monte Carlo methods, Approximation theory, Maximum likelihood, Control systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-104209OAI: oai:DiVA.org:liu-104209DiVA: diva2:695361
Available from: 2014-02-10 Created: 2014-02-10 Last updated: 2014-02-10

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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
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Language
  • de-DE
  • en-GB
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Output format
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