Global stability of bidirectional associative memory neural networks with distributed delays

被引：164

作者：

Zhao, HY ^{[1
]}

机构：

[1] Nanjing Univ, Dept Math, Nanjing 210093, Peoples R China

[2] Xinjiang Normal Univ, Dept Math, Urumqi 830054, Peoples R China

来源：

PHYSICS LETTERS A | 2002年 / 297卷 / 3-4期

基金：

中国国家自然科学基金;

关键词：

global asymptotic stability; neural networks; bidirectional associative memory; inequality;

D O I：

10.1016/S0375-9601(02)00434-6

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

In this Letter, a model describing dynamics of bidirectional associative memory (BAM) neural networks, with distributed delays is considered. Existence and uniqueness of the equilibrium point under more general conditions are also established. Further, we give sufficient criteria of global asymptotic stability (GAS) and uniform stability (US) of an equilibrium point. These criteria can be applied to design globally stable networks and thus have important significance in both theory and applications. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：182 / 190

页数：9

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