Robust stability of delayed fuzzy Cohen-Grossberg neural networks

被引：37

作者：

Huang, Tingwen ^{[1
]}

机构：

[1] Texas A&M Univ Qatar, Doha, Qatar

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2011年 / 61卷 / 08期

基金：

中国国家自然科学基金;

关键词：

Fuzzy Cohen-Grossberg neural networks; Delays; Linear matrix inequality; GLOBAL EXPONENTIAL STABILITY; BOUNDEDNESS;

D O I：

10.1016/j.camwa.2010.09.037

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, using a linear matrix inequality and a differential inequality, we obtain an exponentially robust stability criterion for interval fuzzy Cohen-Grossberg type neural networks with time-varying delays. The criterion can be easily applied to the design of fuzzy general neural networks. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：2247 / 2250

页数：4

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