Global exponential stability of reaction-diffusion recurrent neural networks with time-varying delays

被引：172

作者：

Liang, JL ^{[1
]}

Cao, JD ^{[1
]}

机构：

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

来源：

PHYSICS LETTERS A | 2003年 / 314卷 / 5-6期

关键词：

global exponential stability; reaction-diffusion; neural networks; general Halanay inequality; time-varying delays;

D O I：

10.1016/S0375-9601(03)00945-9

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Employing general Halanay inequality, we analyze the global exponential stability of a class of reaction-diffusion recurrent neural networks with time-varying delays. Several new sufficient conditions are obtained to ensure existence, uniqueness and global exponential stability of the equilibrium point of delayed reaction-diffusion recurrent neural networks. The results extend and improve the earlier publications. In addition, an example is given to show the effectiveness of the obtained result. (C) 2003 Elsevier B.V. All rights reserved.

引用

页码：434 / 442

页数：9

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