Improved Global Exponential Stability Criterion for BAM Neural Networks with Time-Varying Delays

被引：0

作者：

Chen, Yonggang ^{[1
]}

Qin, Tiheng ^{[2
]}

机构：

[1] Henan Inst Sci & Technol, Dept Math, Xinxiang 453003, Peoples R China

[2] Henan Mech & Elect Engn Coll, Dept Basic Course, Xinxiang 453002, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2008, PT I, PROCEEDINGS | 2008年 / 5263卷

关键词：

Exponential stability; BAM neural networks; Time-varying delay; Linear matrix inequality;

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 analysis is investigated for a. class of bidirectional associative memory (BAM) neural networks with time-varying delays. By Using Lyapunov functional method. and by reserving the useful terms when estimating the tipper bound of the derivative of Lyapunov functional, the less conservative exponential stability criterion is derived in terms of linear matrix inequality (LMI). Numerical example is presented to show the effectiveness and the less conservativeness of the proposed method.

引用

页码：128 / +

页数：2

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