Boundedness and global exponential stability for generalized Cohen-Grossberg neural networks with variable delay

被引：38

作者：

Jiang, MH

Shen, Y ^{[1
]}

Liao, XX

机构：

[1] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Wuhan 430074, Hubei, Peoples R China

[2] Three Gorges Univ, Dept Math, Hubei 443000, Peoples R China

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2006年 / 172卷 / 01期

关键词：

Cohen-Grossberg neural networks; global exponential stability; Halanay inequality; dini derivative;

D O I：

10.1016/j.amc.2005.02.009

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A generalized Halanay inequality is established. and the boundedness of generalized Cohen-Grossberg neural networks is investigated. By applying the generalized Halanay inequality and Lyapunov functional method, new sufficient conditions are obtained ensuring the global exponential stability of the solution of the generalized Cohen-Grossberg neural networks with variable delay. Three examples are also given for illustration. (c) 2005 Elsevier Inc. All rights reserved.

引用

页码：379 / 393

页数：15

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