Robust exponential stability of uncertain impulsive neural networks with time-varying delays and delayed impulses

被引：25
作者：
Zhang, Yu [1 ]
机构：
[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
来源：
NEUROCOMPUTING | 2011年 / 74卷 / 17期
基金：
中国国家自然科学基金;
关键词：
Delay; Impulse; Neural network; Stability; Lyapunov function; Razumikhin technique; H-INFINITY-CONTROL; SYSTEMS; STABILIZATION;
D O I：
10.1016/j.neucom.2011.05.004
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 robust exponential stability of uncertain impulsive neural networks with time-varying delays and delayed impulses is considered. It is assumed that the considered impulsive neural networks have norm-bounded parametric uncertainties and time-varying delays and the state variables on the impulses may relate to the time-varying delays. By using Lyapunov functions together with Razumikhin technique or with differential inequalities, some new robust exponential stability criteria are provided. Some examples and their simulations, including examples that the stability of which can not be tackled by the existing results, are also presented to illustrate the effectiveness and the advantage of the obtained results. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：3268 / 3276
页数：9
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