Impulsive stabilization of high-order Hopfield-type neural networks with time-varying delays

被引：70
作者：
Liu, Xinzhi [1 ]
Wang, Qing [1 ]
机构：
[1] Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2008年 / 19卷 / 01期
基金：
加拿大自然科学与工程研究理事会;
关键词：
global exponential stability; impulsive high-order Hopfield-type neural network (NN); impulsive stabilization; Lyapunov-Razumikhin technique;
D O I：
10.1109/TNN.2007.902725
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 studies the problems of global exponential stability for impulsive high-order Hopfield-type neural networks (NNs) with time-varying delays. By employing the Lyapunov-Razumikhin technique, some criteria ensuring global exponential stability are derived. Our results are then used to obtain some sufficient conditions under which some NNs can be forced to converge by impulsive control. Numerical examples are also discussed to illustrate our results.
引用
收藏
页码：71 / 79
页数：9
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