On the global robust asymptotic stability of BAM neural networks with time-varying delays

被引：59
作者：
Lou, Xuyang [1 ]
Cui, Baotong [1 ]
机构：
[1] So Yangtze Univ, Res Ctr Control Sci & Engn, Wuxi 214122, Jiangsu, Peoples R China
来源：
NEUROCOMPUTING | 2006年 / 70卷 / 1-3期
基金：
中国国家自然科学基金;
关键词：
stability; bi-directional associative memory neural network; time-varying delays; Lyapunov functional; linear matrix inequality; Halanay's inequality;
D O I：
10.1016/j.neucom.2006.02.020
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the global robust asymptotic stability of a class of delayed bi-directional associative memory (BAM) neural networks, which contain variable uncertain parameters whose values are unknown but bounded, is studied. Some new sufficient conditions are presented for the global stability of BAM neural networks with time-varying delays by constructing Lyapunov functional and using linear matrix inequality (LMI), Halanay's inequality. A numerical example is presented to illustrate the effectiveness of our theoretical results. (c) 2006 Elsevier B.V.. All rights reserved.
引用
收藏
页码：273 / 279
页数：7
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