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Black-box Models from Input-output Measurements
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2001 (English)Report (Other academic)
Abstract [en]

A black-box model of a system is one that does not use any particular prior knowledge of the character or physics of the relationships involved. It is therefore more a question of "curve- fitting" than "modeling". In this presentation several examples of such black-box model structures will be given. Both linear and non-linear structures are treated. Relationships between linear models, fuzzy models, neural networks and classical non-parametric models are discussed. Some reasons for the usefulness of these model types will also be given. Ways to fit black box structures to measured input-output data are described, as well as the more fundamental (statistical) properties of the resulting models.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2001. , 11 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2362
Keyword [en]
Black-box, Signal processing, Parameter estimation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55842ISRN: LiTH-ISY-R-2362OAI: oai:DiVA.org:liu-55842DiVA: diva2:316697
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-09-04Bibliographically 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