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
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
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