Global exponential stability of Cohen-Grossberg neural networks with variable delays

被引：81
|
作者：
Zhang, JY [1 ]
Suda, Y
Komine, H
机构：
[1] SW Jiaotong Univ, Natl Traction Power Lab, Chengdu 610031, Peoples R China
[2] Univ Tokyo, Suda Lab, Ctr Collaborat Res, Meguro Ku, Tokyo 1538505, Japan
[3] Univ Tokyo, Inst Ind Sci, Meguro Ku, Tokyo 1538505, Japan
来源：
PHYSICS LETTERS A | 2005年 / 338卷 / 01期
基金：
中国国家自然科学基金;
关键词：
neural network; Cohen-Grossberg neural networks; time delay; global asymptotical stability; global exponential stability; M-matrix;
D O I：
10.1016/j.physleta.2005.02.005
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this Letter, the conditions ensuring existence, uniqueness of the equilibrium point of Cohen-Grossberg neural networks with variable delays are obtained under more general assumption about activation functions. Applying idea of vector Liapunov function, and M-matrix theory, the sufficient conditions for global exponential stability of Cohen-Grossberg neural networks are obtained. These results generalize a few previous known results and remove some restrictions on the neural networks. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码：44 / 50
页数：7
相关论文
共 50 条
12345