A Fuzzy Wavelet Neural Network Model for System Identification

被引：6
|
作者：
Yilmaz, Sevcan [1 ]
Oysal, Yusuf [1 ]
机构：
[1] Anadolu Univ, Dept Comp Engn, Eskisehir, Turkey
来源：
2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS | 2009年
关键词：
DYNAMICAL-SYSTEMS; DESIGN; TIME;
D O I：
10.1109/ISDA.2009.96
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a fuzzy wavelet neural network model is proposed for system identification problems. The proposed model is obtained from the traditional Takagi-Sugeno-Kang (TSK) fuzzy system by replacing the consequent part of fuzzy rules with wavelet basis functions that have time-frequency localization properties. We use a radial function of Mexican Hat wavelet in the consequent part of each rule. A fast gradient algorithm based on quasi-Newton methods is used to obtain the optimal values for unknown parameters of the model. Simulation results of some benchmark problems in the literature are also given to illustrate the effectiveness of the model.
引用
收藏
页码：1284 / 1289
页数：6
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