Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

被引：12

作者：

Wan, Li ^{[1
]}

Zhou, Qinghua

机构：

[1] Wuhan Univ Sci & Technol, Dept Math & Phys, Wuhan 430073, Peoples R China

[2] Nanjing Univ, Dept Math, Nanjing 210008, Peoples R China

来源：

PHYSICS LETTERS A | 2007年 / 371卷 / 1-2期

基金：

中国国家自然科学基金;

关键词：

bidirectional associate memory; exponential stability; time-varying delay; diffusion;

D O I：

10.1016/j.physleta.2007.06.008

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established. (C) 2007 Elsevier B.V. All rights reserved.

引用

页码：83 / 89

页数：7

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