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
收藏
页码：2247 / 2250
页数：4
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