Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case

被引：46
|
作者：
Raja, R. [1 ]
Anthoni, S. Marshal [2 ]
机构：
[1] Periyar Univ, Dept Math, Salem 636011, India
[2] Anna Univ, Dept Math, Coimbatore 641047, Tamil Nadu, India
来源：
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2011年 / 16卷 / 02期
关键词：
Discrete-time BAM neural networks; Global exponential stability; Linear matrix inequality; Time-varying delays; BIDIRECTIONAL ASSOCIATIVE MEMORIES; ASYMPTOTIC STABILITY; LMI APPROACH; ROBUST STABILITY; VARIABLE DELAYS; CRITERIA;
D O I：
10.1016/j.cnsns.2010.04.022
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the global exponential stability of discrete-time BAM neural networks. The proposed LMI based results can be easily checked by LMI control toolbox. Moreover, an example is also provided to demonstrate the effectiveness of the proposed method. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码：613 / 622
页数：10
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