Stability analysis of impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays

被引：13

作者：

Song, Qiankun ^{[2
]}

Cao, Jinde ^{[1
]}

机构：

[1] SE Univ, Dept Math, Nanjing 210096, Peoples R China

[2] Chongqing Jiaotong Univ, Dept Math, Chongqing 400074, Peoples R China

来源：

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS | 2007年 / 17卷 / 05期

关键词：

Cohen-Grossberg neural network; impulsive; unbounded time-varying delays; exponential stability;

D O I：

10.1142/S012906570700124X

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, the impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays is considered. By using the analysis method and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of the addressed neural network. These results generalize the existing relevant stability results. Two examples with simulations are given to show the effectiveness of the obtained results.

引用

页码：407 / 417

页数：11

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