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Neural Networks in System Identification
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.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1994 (English)Report (Other academic)
Abstract [en]

Neural Networks are non-linear black-box model structures, to be used with conventional parameter estimation methods. They have good general approximation capabilities for reasonable non-linear systems. When estimating the parameters in these structures, there is also good adaptability to concentrate on those parameters that have the most importance for the particular data set.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1994. , 24 p.
Series
LiTH-ISY-R, ISSN 1400-3902 ; 1622
Keyword [en]
Neural networks, Parameter estimation, Model structures, Non-linear systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-55185ISRN: LiTH-ISY-R-1622OAI: oai:DiVA.org:liu-55185DiVA: diva2:315793
Available from: 2010-04-29 Created: 2010-04-29 Last updated: 2014-10-07Bibliographically approved

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Ljung, Lennart

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • Other style
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Language
  • de-DE
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  • nn-NB
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Output format
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