AND-OR fuzzy neural networks

被引：0
|
作者：
Sui Jianghuai [1 ]
Ren Guang [1 ]
机构：
[1] Dalian Maritime Univ, Marine Engn Coll, Dalian 116026, Peoples R China
来源：
PROCEEDINGS OF THE FIRST INTERNATIONAL SYMPOSIUM ON TEST AUTOMATION & INSTRUMENTATION, VOLS 1 - 3 | 2006年
关键词：
in-degree; relevant degree; connectivity;
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：
A novel multilayer feed-forward AND-OR fuzzy neural network (AND-OR FNN) is proposed in this paper. The equivalent is proved between the architecture of AND-OR FNN and fuzzy weighted Mamdani inference. The main superiority is shown not only in reducing the input space by special inner structure of neurons. but also auto-extracting the rule base by the structure optimization of network.
引用
收藏
页码：1937 / 1941
页数：5
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