Stability of Impulsive Cohen-Grossberg Neural Networks with Delays

被引:0
|
作者
Yang, Jianfu [1 ]
Ding, Wensi [2 ]
Yang, Fengjian [1 ]
Liang, Lishi [3 ]
Hong, Qun [4 ]
机构
[1] Zhongkai Univ Agr & Engn, Dept Computat Sci, Guangzhou 510225, Guangdong, Peoples R China
[2] South China Univ Technol, Sch Mach & Automat Engn, Guangzhou 510640, Peoples R China
[3] 5th Mid Sch Guangzhou City, Guangzhou 510220, Guangdong, Peoples R China
[4] Haizhu Dist Chigang Primary Sch Guangzhou City, Guangzhou 510310, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
global exponential stability; Lyapunov function; GLOBAL EXPONENTIAL STABILITY;
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, with assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, Young inequality and Halanay differential inequality with delay, the global exponential stability of the equilibrium point for a class of Cohen-Grossberg neural networks with time-varying delays and impulses is investigated, the sufficient conditions for globally exponential stability of neural networks are obtained.
引用
收藏
页码:554 / +
页数:2
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