Global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms

被引：59

作者：

Wang, Jian ^{[1
]}

Lu, Jun Guo ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China

来源：

CHAOS SOLITONS & FRACTALS | 2008年 / 38卷 / 03期

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1016/j.chaos.2007.01.032

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper, we study the global exponential stability of fuzzy cellular neural networks with delays and reaction-diffusion terms. By constructing a suitable Lyapunov functional and utilizing some inequality techniques, we obtain a sufficient condition for the uniqueness and global exponential stability of the equilibrium solution for a class of fuzzy cellular neural networks with delays and reaction-diffusion terms. The result imposes constraint conditions on the network parameters independently of the delay parameter. The result is also easy to check and plays an important role in the design and application of globally exponentially stable fuzzy neural circuits. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：878 / 885

页数：8

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