Global exponential stability of impulsive Cohen-Grossberg neural networks with continuously distributed delays

被引：16

作者：

Ping, Zhao Wu ^{[1
]}

Lu, Jun Guo ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China

来源：

CHAOS SOLITONS & FRACTALS | 2009年 / 41卷 / 01期

关键词：

TIME-VARYING DELAYS; ASYMPTOTIC STABILITY; PERIODIC-SOLUTIONS; HARMLESS DELAYS; EXISTENCE;

D O I：

10.1016/j.chaos.2007.11.022

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper, several classes of impulsive Cohen-Grossberg neural networks with continuously distributed delays are considered. Global exponential stability and robust global exponential stability of the equilibrium solution are investigated by using Lyapunov function and integro-differential inequality. Moreover, sufficient conditions are also given to guarantee the existence of (omega) over bar -periodic solution and that all other solutions are convergent to it globally exponentially. Finally, two examples are given to demonstrate the effectiveness of our results in this paper. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：164 / 174

页数：11

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