Please use this identifier to cite or link to this item:
|Title:||Adaptive neuro-fuzzy identification method of hammerstein model|
|Authors:||Jia, L. |
|Source:||Jia, L.,Chiu, M.-S.,Ge, S.S.,Wang, Z. (2004). Adaptive neuro-fuzzy identification method of hammerstein model. 2004 IEEE Conference on Cybernetics and Intelligent Systems : 936-941. ScholarBank@NUS Repository.|
|Abstract:||In this paper, adaptive neuro-fuzzy identification is investigated for the Hammerstein model, which consists of the cascade structure of a static nonlinearity followed by a linear dynamic part. Utilizing the approximation ability of neuro-fuzzy for the nonlinear static function, there is no need for prior knowledge and restriction on static nonlinear function. Furthermore, an adaptive algorithm designed by Lyapunov stability theory is proposed to obtain the neuro-fuzzy Hammerstein model. Example is used to illustrate the performance and applicability of the proposed neuro-fuzzy Hammerstein model.|
|Source Title:||2004 IEEE Conference on Cybernetics and Intelligent Systems|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 9, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.