Global exponential stability of Hopfield reaction-diffusion neural networks with time-varying delays

被引：87

作者：

Wang, LS ^{[1
]}

Xu, DY

机构：

[1] Ocean Univ China, Dept Math, Qingdao 266071, Peoples R China

[2] Liaocheng Univ, Dept Math, Liaocheng 252059, Peoples R China

[3] Sichuan Univ, Math Coll, Chengdu 610064, Peoples R China

来源：

SCIENCE IN CHINA SERIES F-INFORMATION SCIENCES | 2003年 / 46卷 / 06期

关键词：

neural networks; reaction-diffusion; delay; stability;

D O I：

10.1360/02yf0146

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 authors analyze the existence of the equilibrium point and global exponential stability for Hopfield reaction-diffusion neural networks with time-varying delays by means of the topological degree theory and generalized Halanay inequality. Since the diffusion phenomena and time delay could not be ignored in neural networks and electric circuits, the model presented here is close to the actual systems, and the sufficient conditions on global exponential stability established in this paper, which are easily verifiable, have a wider adaptive range.

引用

页码：466 / 474

页数：9

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