Novel global asymptotic stability conditions for hopfield neural networks with time delays

被引：0
|
作者：
Gao, Ming [1 ]
Cui, Baotong [1 ]
Sheng, Li [1 ]
机构：
[1] So Yangtze Univ, Res Ctr Control Sci & Engn, 1800 Lihu Rd, Wuxi 214122, Jiangsu, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2007, PT 1, PROCEEDINGS | 2007年 / 4491卷
基金：
中国国家自然科学基金;
关键词：
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 asymptotic stability of Hopfield neural networks with time delays is investigated. Some novel sufficient conditions are presented for the global stability of a given delayed Hopfield neural networks by constructing Lyapunov functional and using some well-known inequalities. A linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the given neural networks. An illustrative example is provided to demonstrate the effectiveness of our theoretical results.
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页码：935 / +
页数：2
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