Resilient back propagation learning algorithm for recurrent fuzzy neural networks

被引：17
|
作者：
Mastorocostas, PA [1 ]
机构：
[1] Technol & Educ Inst Serres, Dept Informat & Commun, Serres 62124, Greece
来源：
ELECTRONICS LETTERS | 2004年 / 40卷 / 01期
关键词：
D O I：
10.1049/el:20040052
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An efficient training method for recurrent fuzzy neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static neural networks, in order to be applied to dynamic systems. A comparative analysis with the standard back propagation through time is given, indicating the effectiveness of the proposed algorithm.
引用
收藏
页码：57 / 58
页数：2
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