Global exponential stability for BAM neural networks with time-varying delays

被引：0

作者：

Zong, Guangdeng ^{[1
,2
]}

Wu, Yanfeng ^{[2
]}

Hou, Linlin ^{[2
]}

机构：

[1] Nanjing Univ Sci & Technol, Sch Automat, Nanjing 210094, Peoples R China

[2] Qufu Normal Univ, Qufu 273165, Peoples R China

来源：

2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11 | 2008年

关键词：

BAM neural networks; time-varying delay systems; Lyapunov function; exponential stability;

D O I：

10.1109/CCDC.2008.4597775

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The exponential stability problem for a class of BAM neural networks with time-varying delays is considered. Based on the Lyapunov function method, several sufficient conditions are provided ensuring the delayed BAM neural networks to have a unique equilibrium point, which is globally exponentially stable. All the results are given in terms of LMIs, which can be easily solved by resorting to Matlab tool-box. Simulations validate the correctness of the presented algorithm.

引用

页码：2500 / 2505

页数：6

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