Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays

被引：8
|
作者：
Chen, Yonggang [1 ]
Bi, Weiping [2 ]
Wu, Yuanyuan [3 ]
机构：
[1] Henan Inst Sci & Technol, Dept Math, Xinxiang 453003, Peoples R China
[2] Henan Normal Univ, Coll Math & Informat Sci, Xinxiang 453007, Peoples R China
[3] Southeast Univ, Sch Automat, Minist Educ, Key Lab Measurement & Control Complex Syst Engn, Nanjing 210096, Peoples R China
来源：
DISCRETE DYNAMICS IN NATURE AND SOCIETY | 2008年 / 2008卷
基金：
中国国家自然科学基金;
关键词：
D O I：
10.1155/2008/421614
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI). Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method. Copyright (C) 2008 Yonggang Chen et al.
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页数：14
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