Global exponential stability of a class of Hopfield neural networks with delays

被引：3
|
作者：
Liu, Wei [1 ]
Fu, Chaojin [1 ]
Hu, Hongchang [1 ]
机构：
[1] Hubei Normal Univ, Coll Math & Stat, Huangshi, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2011年 / 20卷 / 08期
关键词：
Hopfield neural networks; Global exponential stability; Delays; TIME-VARYING DELAYS; IMPULSES;
D O I：
10.1007/s00521-010-0470-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper investigates global exponential stability of a class of Hopfield neural networks with delays based on contraction mapping principle, Lyapunov function and inequality technique. Some sufficient conditions are derived that ensure the existence, uniqueness, global exponential stability of equilibrium point of the neural networks. Finally, an illustrative numerical example is given to demonstrate the effectiveness of our results.
引用
收藏
页码：1205 / 1209
页数：5
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