A novel criterion for global asymptotic stability of BAM neural networks with tine delays

被引：97

作者：

Park, JH ^{[1
]}

机构：

[1] Yeungnam Univ, Dept Elect Engn, Robust Control & Nonlinear Dynam Lab, Kyongsan 712749, South Korea

来源：

CHAOS SOLITONS & FRACTALS | 2006年 / 29卷 / 02期

关键词：

D O I：

10.1016/j.chaos.2005.08.018

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A delay-differential equation modelling a bidirectional associative memory (BAM) neural networks is investigated. An asymptotic stability of the BAM neural networks with time delays is considered by constructing a new suitable Lyapunov functional and some matrix inequality technique. A novel delay-dependent stability criterion is given in terms of matrix inequalities, which can be solved easily by various optimization algorithms. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：446 / 453

页数：8

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