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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)In: Proceedings of the 8th IFAC Symposium on Identification and System Parameter Estimation, 1988, 971-976 p.Conference paper, Published paper (Refereed)
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
1988. 971-976 p.
Keyword [en]
Mathematical statistics, Monte Carlo methods, Approximation theory, Maximum likelihood, Control systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-100577OAI: oai:DiVA.org:liu-100577DiVA: diva2:663114
Conference
8th IFAC Symposium on Identification and System Parameter Estimation, 27-31 August, 1988, Beijing, China
Available from: 2013-11-09 Created: 2013-11-09 Last updated: 2014-02-16

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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  • Other style
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Language
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Output format
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