Title :
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
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;
Conference_Titel :
Electrical Engineering and Software Applications (ICEESA), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-6302-0
DOI :
10.1109/ICEESA.2013.6578477
