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Model Order Selection of N-FIR Models by the Analysis of Variance Method
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1999 (English)Report (Other academic)
Abstract [en]

Identification of non-linear finite impulse response (N-FIR) models is studied. In particular the selection of model structure, i.e., to find the contributing input time lags, is examined. A common method, exhaustive search among models with all possible combinations of the input time lags, has some undesired drawbacks, as a tendency that the minimization algorithm gets stuck in local minima and heavy computations. To avoid these drawbacks we need to know the model structure prior to identifying a model. In this report we show that a statistical method, the multivariate analysis of variance, is a good alternative to exhaustive search in the identification of the structure of non-linear FIR-models. We can reduce the risks of getting an erroneous model structure due to the non-convexity of the minimization problems, reduce the computation time needed and also get a good estimate of how far we can enhance the fit of the desired model.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 1999. , 10 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2210
Keyword [en]
Model order selection, Identification, Non-linear FIR models, Analysis of variance
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55855ISRN: LiTH-ISY-R-2210OAI: oai:DiVA.org:liu-55855DiVA: diva2:316681
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-09-04Bibliographically approved

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Lind, Ingela

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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