Hybrid learning algorithm for interval type-2 fuzzy neural networks

被引：14
作者：
Castro, Juan R.
Castillo, Oscar
Melin, Patricia
Rodriguez-Diaz, Antonio
机构：
来源：
GRC: 2007 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, PROCEEDINGS | 2007年
关键词：
D O I：
10.1109/GrC.2007.116
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a class of Interval Type-2 Fuzzy Neural Networks (IT2FNN) is proposed, which is functionally equivalent to interval type-2 fuzzy inference systems. The computational process envisioned for a fuzzy-neural system is as follows: it starts with the development of an "Interval Type-2 Fuzzy Neuron", which is based on biological neural morphologies, followed by learning mechanisms. We describe how to decompose the parameter set such that the hybrid learning rule of adaptive networks can be applied to the IT2FNW architecture.
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收藏
页码：157 / 162
页数：6
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