Author/Authors :
Li Jia، نويسنده , , Min-Sen Chiu and Shuzhi Sam Ge، نويسنده ,
DocumentNumber :
1384690
Title Of Article :
A noniterative neuro-fuzzy based identification method for Hammerstein processes
شماره ركورد :
11330
Latin Abstract :
In this paper, a noniterative identification procedure for neuro-fuzzy based Hammerstein model is presented. The proposed method not only avoids the inevitable restrictions on static nonlinear function encountered by using the polynomial approach, but also overcomes the problems of initialization and convergence of the model parameters, which are usually resorted to trial and error procedure in the existing iterative algorithms used for the identification of Hammerstein model. To construct the neuro-fuzzy based model, a clustering algorithm is presented to estimate the centers and widths of the model, and an analytical solution is developed to calculate the weights of the model in a noniterative manner. Examples are used to illustrate the applicability of the proposed method and a comparison with polynomial approach is made.
From Page :
749
NaturalLanguageKeyword :
Hammerstein model , Nonlinear Processes , Noniterative identification , Neuro-fuzzy system
JournalTitle :
Studia Iranica
To Page :
761
To Page :
761
Link To Document :
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