Global asymptotic stability of delayed bi-directional associative memory neural networks

被引：163

作者：

Cao, JD ^{[1
]}

机构：

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

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2003年 / 142卷 / 2-3期

关键词：

bi-directional associative memory; neural network; global asymptotic stability; equilibrium; axonal signal transmission delay;

D O I：

10.1016/S0096-3003(02)00308-9

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In the paper, the global asymptotic stability and the existence of equilibrium are considered for continuous bi-directional associative memory (BAM) neural networks with axonal signal transmission delay by using Lyapunov method. New sufficient conditions are derived to ascertain the global asymptotic stability of BAM, and the obtained results are less restrictive than those reported in the literature. (C) 2002 Elsevier Science Inc. All rights reserved.

引用

页码：333 / 339

页数：7

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