DocumentCode
3463484
Title
Online identification of nonlinear system in the Reproducing Kernel Hilbert Space using SVDKPCA method
Author
Taouali, Okba ; Elaissi, Ilyes ; Messaoud, Hassani
Author_Institution
Res. Unit ATSI, Nat. Eng. Sch. of Monastir, Monastir, Tunisia
fYear
2011
fDate
3-5 March 2011
Firstpage
1
Lastpage
6
Abstract
This paper proposes a new method for online identification of a nonlinear system modelled on Reproducing Kernel Hilbert Space (RKHS). The proposed SVD-KPCA method uses the SVD technique to update the principal components. Then we use the Reduced Kernel Principal Component Analysis (RKPCA) to approach the principal components which represent the observations selected by the KPCA method.
Keywords
Hilbert spaces; identification; nonlinear systems; principal component analysis; singular value decomposition; SVD-KPCA method; online nonlinear system identification; reduced kernel principal component analysis; reproducing kernel Hilbert space; Chemical reactors; Data models; Eigenvalues and eigenfunctions; Hilbert space; Kernel; Least squares approximation; Principal component analysis; Online SVD-KPCA; RKHS; RKPCA; SLT;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Computing and Control Applications (CCCA), 2011 International Conference on
Conference_Location
Hammamet
Print_ISBN
978-1-4244-9795-9
Type
conf
DOI
10.1109/CCCA.2011.6031191
Filename
6031191
Link To Document