Comparative study of minimal value parameters and RKPCA in RKHS

Author

Souilem, Nadia ; Elaissi, Ilyes ; Messaoud, Hassani

Author_Institution

Unite de Rech. d´Autom. Traitement de Signal et Image (ATSI), Ecole Nat. d´Ingenieur Monastir, Monastir, Tunisia

fYear

2013

fDate

21-23 March 2013

Firstpage

1

Lastpage

6

Abstract

This paper aims to compare two RKHS models used for describing nonlinear process behaviour. The first model is issued from the estimation of the minimal value of the learning set cardinal and the second results from the complexity reduction of an RKHS model built using arbitrary learning set cardinal. Both models have been tested on non linear dynamic system used as a benchmark and the results were successful.

Keywords

Hilbert spaces; computational complexity; learning systems; nonlinear dynamical systems; principal component analysis; RKHS model complexity reduction; RKPCA; comparative study; learning set cardinal; minimal value parameters; nonlinear dynamic system; nonlinear process behaviour; reduced kernel principal component analysis; reproducing kernel Hilbert space; Biological system modeling; Eigenvalues and eigenfunctions; Hilbert space; Kernel; Principal component analysis; Signal to noise ratio; Vectors; Complexity reduction; Determinant ratio; Jump; Model order; Nonlinear system; RKHS; RKPCA;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering and Software Applications (ICEESA), 2013 International Conference on

Conference_Location

Hammamet

Print_ISBN

978-1-4673-6302-0

Type

conf

DOI

10.1109/ICEESA.2013.6578477

Filename

6578477