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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)In: Proceedings of the 10th IFAC Symposium on System Identification, 1994, Vol. 2, 49-72 p.Conference paper, Published paper (Refereed)
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
1994. Vol. 2, 49-72 p.
Keyword [en]
Neural networks, Parameter estimation, Model structures, Non-linear systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-94049ISBN: 978-0080422251 (print)OAI: oai:DiVA.org:liu-94049DiVA: diva2:630034
Conference
10th IFAC Symposium on System Identification, Copenhagen, Denmark, July, 1994
Available from: 2013-06-18 Created: 2013-06-16 Last updated: 2013-06-18

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Ljung, Lennart

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