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
收藏
页码：2500 / 2505
页数：6
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