Delay-independent stability analysis of Cohen-Grossberg neural networks

被引:251
作者
Chen, TP [1 ]
Rong, LB [1 ]
机构
[1] Fudan Univ, Inst Math, Lab Nonlinear Sci, Shanghai 200433, Peoples R China
基金
中国国家自然科学基金;
关键词
neural networks; time delay; stability; linear matrix equality; Cohen-Grossberg; Lyapunov functional;
D O I
10.1016/j.physleta.2003.08.066
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In this Letter, we discuss a class of Cohen-Grossberg neural networks with time delays and investigate their global asymptotic stability of the equilibrium point for this systems. By introducing a new type of Lyapunov functionals, a set of sufficient conditions guaranteeing the global asymptotic convergence are derived. Our criteria represent an extension of the existing results in literatures. Combined with the linear matrix inequality technique, a new generalized, LMI based, criterion is obtained. The presented result: is more easily to verified and turns out to be less restrictive than those given in the earlier literature. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:436 / 449
页数:14
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