Global Exponential Stability of A Class of Impulsive Cohen-Grossberg Neural Networks with Unbounded Delays

被引：0
|
作者：
Xu, Xiaohui [1 ]
Zhang, Jiye [1 ]
Zhang, Keyue [1 ]
机构：
[1] SW Jiaotong Univ, Natl Tract Power Lab, Chengdu 610031, Peoples R China
来源：
2008 3rd International Conference on Intelligent System and Knowledge Engineering, Vols 1 and 2 | 2008年
关键词：
D O I：
10.1109/ISKE.2008.4731048
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 a class of impulsive Cohen-Grossberg neural networks, which contains both variable and unbounded delays. By constructing vector Lyapunov functions and nonlinear integro-differential inequalities, the sufficient conditions for global exponential stability are obtained. An example is given to demonstrate the effectiveness of the proposed conditions.
引用
收藏
页码：851 / 855
页数：5
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