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.
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页码：446 / 453
页数：8
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