Exponential Stability Analysis for Discrete-Time Stochastic BAM Neural Networks with Time-Varying Delays

被引：0
|
作者：
Qin, Tiheng [1 ]
Pan, Quanxiang [2 ]
Chen, Yonggang [2 ]
机构：
[1] Henan Mech & Elect Engn Coll, Basic Dept, Xinxiang 453002, Peoples R China
[2] Henan Inst Sci & Technol, Dept Math, Xining, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2010, PT 1, PROCEEDINGS | 2010年 / 6063卷
关键词：
Expotiential stability; Discrete-time BAM neural networks; Stochastic disturbances; Time-varying delays; LMIs; GLOBAL ASYMPTOTIC STABILITY; ROBUST STABILITY; VARIABLE DELAYS;
D O I：
暂无
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 exponential stability at problem is investigated for discrete-time stochastic BAM neural networks With time-varying delays. By constructing the appropriate Lyapunov functional, and by resorting to free weight matrix method, the delay-dependent exponential stability criteria are derived in terms of linear matrix inequalities (LMIs). Numerical examples are presented to show the effectiveness and benefits of ours results.
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页码：659 / +
页数：2
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