A TSK-Type fuzzy neural network (TFNN) systems for dynamic systems identification

被引：0
|
作者：
Lee, CH [1 ]
Lai, WY [1 ]
Lin, YC [1 ]
机构：
[1] Yuan Ze Univ, Dept Elect Engn, Chungli 320, Taoyuan, Taiwan
来源：
42ND IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-6, PROCEEDINGS | 2003年
关键词：
fuzzy neural network; TSK-type fuzzy systems; back-propagation algorithm; system identification;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a TSK-type fuzzy neural network system (TFNN) for identifying unknown dynamic systems is proposed. The TFNN system can learn its knowledge base from input-output training data. Thus, the unknown system is represented as several if-then rules with TSK-type consequent parts. The TFNN system can be randomly initialized and then trained by the back-propagation algorithm. Several examples are presented to illustrate the effectiveness of our approach.
引用
收藏
页码：4002 / 4007
页数：6
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