EXPONENTIAL SYNCHRONIZATION OF DELAYED REACTION-DIFFUSION NEURAL NETWORKS WITH GENERAL BOUNDARY CONDITIONS

被引：0

作者：

Yan, Ping ^{[1
]}

Lv, Teng ^{[2
]}

机构：

[1] Anhui Agr Univ, Sch Sci, Hefei 230036, Peoples R China

[2] Army Officer Acad, Teaching & Res Sect Comp, Hefei 230031, Peoples R China

来源：

ROCKY MOUNTAIN JOURNAL OF MATHEMATICS | 2013年 / 43卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Exponential synchronization; delayed neural networks; general boundary condition; Lyapunov functional; TIME-VARYING DELAYS; STABILITY;

D O I：

10.1216/RMJ-2013-43-3-1037

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper, we study delayed reaction-diffusion neural networks with general boundary conditions including Dirichlet and Neumann boundary conditions. By using some inequality techniques and constructing suitable Lyapunov functionals, some sufficient conditions are given to ensure the exponential synchronization of the drive-response neural networks. Finally, an example is given to verify the theoretical analysis.

引用

页码：1037 / 1057

页数：21

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