Nonlinear set-membership estimation: A support vector machine approach

Verfasser / Beitragende:
[K. J. Keesman, R. Stappers]
Ort, Verlag, Jahr:
2004
Enthalten in:
Journal of Inverse and Ill-posed Problems, 12/1(2004-02-01), 27-41
Format:
Artikel (online)
ID: 378883267
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245 0 0 |a Nonlinear set-membership estimation: A support vector machine approach  |h [Elektronische Daten]  |c [K. J. Keesman, R. Stappers] 
520 3 |a In this paper a support vector machine (SVM) approach for characterizing the feasible parameter set (FPS) in non-linear set-membership estimation problems is presented. It iteratively solves a regression problem from which an approximation of the boundary of the FPS can be determined. To guarantee convergence to the boundary the procedure includes a no-derivative line search and for an appropriate coverage of points on the FPS boundary it is suggested to start with a sequential box pavement procedure. The SVM approach is illustrated on a simple sine and exponential model with two parameters and an agro-forestry simulation model. 
540 |a Copyright 2004, Walter de Gruyter 
700 1 |a Keesman  |D K. J.  |u Systems and Control Group, Wageningen University, P.O. Box 43, 6700 AA Wageningen, The Netherlands. E-mail: karel.keesman@wur.nl  |4 aut 
700 1 |a Stappers  |D R.  |u Systems and Control Group, Wageningen University, P.O. Box 43, 6700 AA Wageningen, The Netherlands. E-mail: karel.keesman@wur.nl  |4 aut 
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950 |B NATIONALLICENCE  |P 700  |E 1-  |a Stappers  |D R.  |u Systems and Control Group, Wageningen University, P.O. Box 43, 6700 AA Wageningen, The Netherlands. E-mail: karel.keesman@wur.nl  |4 aut 
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