The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON SYSTEMS
Transactions ID Number: 32-568
Full Name: Hassani Messaoud
Position: Professor
Age: ON
Sex: Male
Address: Ecole national d'ingénieur de Monastir 5000, Tunisie
Country: TUNISIA
Tel: 00 216 73 500 511
Tel prefix:
Fax: 00 216 73 500 514
E-mail address: hassani.messaoud@enim.rnu.tn
Other E-mails: taoualiokba@yahoo.fr
Title of the Paper: identification of non linear miso process using rkhs and volterra models
Authors as they appear in the Paper: Okba Taouali, Nabiha Saidi , Hassani Messaoud
Email addresses of all the authors: taoualiokba@yahoo.fr, saidinabiha@yahoo.fr, hassani.messaoud@enim.rnu.tn
Number of paper pages: 10
Abstract: This paper treats the comparison between the Volterra model and Reproducing Kernel Hilbert Space (RKHS) model in Multiple Input Single Output (MISO) case. The RKHS model uses the Statistical learning theory to find a solution of a regularization risk. It is characterise by a linear combination of the kernels function. The complexity of Volterra model is depending of the degree and the memory of the model contrarily of the RKHS model which depend only of the number of observations. The performances of both models are evaluated first by using Monte Carlo numerical simulations and then have been tested for modelling of a chemical reactor and results are successful.
Keywords: Statistical Learning Theory, RKHS, Volterra, MISO, modelling, Chemical reactor
EXTENSION of the file: .pdf
Special (Invited) Session:
Organizer of the Session:
How Did you learn about congress:
IP ADDRESS: 41.229.65.10
