pth moment exponential stability of stochastic cohen-grossberg neural networks with time-varying delays

被引：31

作者：

Zhu, Enwen ^{[1
]}

Zhang, Haomin

Wang, Yong

Zou, Jiezhong

Yu, Zheng

Hou, Zhenting

机构：

[1] Changsha Univ Sci & Technol, Sch Math & Comp Sci, Changsha 410076, Hunan, Peoples R China

[2] Cent S Univ, Sch Math, Changsha 410075, Hunan, Peoples R China

[3] Harbin Inst Technol, Dept Math, Harbin 150001, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2007年 / 26卷 / 03期

基金：

中国国家自然科学基金;

关键词：

stochastic Cohen-Grossberg neural networks; pth moment exponential stability; Razumikhin-type theorem;

D O I：

10.1007/s11063-007-9051-z

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The pth moment exponential stability of stochastic Cohen-Grossberg with time-varying delays is investigated in this paper. A set of novel sufficient conditions on pth moment exponential stability are given for the considered system by using the well-known Razumikhin-type theorem. Finally, two examples with their numerical simulations are provided to show the correctness of our analysis.

引用

页码：191 / 200

页数：10

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