Nonlinear set-membership estimation: a support vector machine approach

Keesman, K. J. and Stappers, R. (2004) Nonlinear set-membership estimation: a support vector machine approach. Journal of inverse and ill-posed problems, 12 (1). pp. 27-42. ISSN 1569-3945 doi: 10.1515/156939404773972752

Abstract/Summary

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.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/28439
Identification Number/DOI	10.1515/156939404773972752
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO) Science > School of Mathematical, Physical and Computational Sciences > Department of Mathematics and Statistics
Publisher	De Gruyter
Download/View statistics	View download statistics for this item