Globally Exponential Stability of a Class of Impulsive Neural Networks with Variable Delays

被引：0

作者：

Yang, Jianfu ^{[1
]}

Yang, Fengjian ^{[1
]}

Zhang, Chaolong ^{[1
]}

Wu, Dongqing ^{[1
]}

Gao, Chuanxiang ^{[1
]}

机构：

[1] Zhongkai Univ Agr & Engn, Dept Computat Sci, Guangzhou 510225, Guangdong, Peoples R China

来源：

CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年

关键词：

Impulse; Neural networks; Time-varying delays; Globally exponential stability; Lyapunov function; TIME-VARYING DELAYS; DYNAMICS;

D O I：

10.1109/CCDC.2009.5194641

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 main purpose of this paper is to study the globally exponential stability of the equilibrium point for a class of impulsive neural networks with time-varying delays. Without assuming global Lipschitz conditions on the activation functions,applying idea of vector Lyapunov function,combining Young inequality and Halanay differential inequality with delay,the sufficient conditions for globally exponential stability of neural networks are obtained.

引用

页码：3166 / 3170

页数：5

共 23 条

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