The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 89-835
Full Name: Okba Taouali
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: Ecole nationale d'Ingénieurs de Monastir
Country: TUNISIA
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E-mail address: taoualiokba@yahoo.fr
Other E-mails: taouali_enim@yahoo.fr
Title of the Paper: a new approach for identification of MIMO non linear system with RKHS model
Authors as they appear in the Paper: Okba Taouali,Ilyes Elaissi,Tarek Garna,Hassani Messaoud
Email addresses of all the authors: taoualiokba@yahoo.fr,ilyes.elaissi@yahoo.fr,tarek.garna@enim.rnu.tn,hassani.messaoud@enim.rnu.tn
Number of paper pages: 10
Abstract: In this paper we propose a new approach for the modelling of the multi-variable systems (MIMO) on the Reproducing Kernel Hilbert Space (RKHS). The proposed approach considers the MIMO system as a set of MISO processes modelled in RKHS space. We propose also a comparative study of three identification kernel methods of nonlinear systems modelled in Reproducing Kernel Hilbert Space (RKHS), where the model output results from a linear combination of kernel functions. Theses methods are support vector machines (SVM), regularization networks (RN) and kernel Principal Component Analysis (KPCA). The performances of the proposed MIMO RKHS model and of each kernel method in terms of generalization ability and computing time were evaluated on numerical simulations.
Keywords: Identification,Rkhs,Slt,Mimo model,Svm, Rn,Kpca
EXTENSION of the file: .pdf
Special (Invited) Session: Supervised Learning with Kernel methods
Organizer of the Session: ID: 633-393
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