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Direct Weight Optimization in Nonlinear Function Estimation and System Identification
Institute of Control Sciences, Russia.
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.
2007 (English)In: Proceedings of the 6th International Conference on System Identification and Control Problems (SICPRO '07), 2007Conference paper, Published paper (Refereed)
Abstract [en]

The Direct Weight Optimization (DWO) approach to estimating a regression function and its application to nonlinear system identification has been proposed and developed during the last few years by the authors. Computationally, the approach is typically reduced to a quadratic or conic programming and can be effectively realized. The obtained estimates demonstrate optimality or sub-optimality in a minimax sense w.r.t. the mean-square error criterion under weak design conditions. Here we describe the main ideas of the approach and represent an overview of the obtained results.

Place, publisher, year, edition, pages
2007.
Keyword [en]
Function estimation, Non-parametric identification, Minimax techniques, Quadratic programming, Nonlinear systems, Mean-square error
National Category
Engineering and Technology Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-42215Local ID: 61633OAI: oai:DiVA.org:liu-42215DiVA: diva2:263070
Conference
6th International Conference on System Identification and Control Problems (SICPRO '07), Moscow, Russia, January-February, 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-03-20

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Roll, JacobLjung, Lennart

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