Exponential and fixed-time synchronization of Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms

被引：87

作者：

Li, Ruoxia ^{[1
,2
]}

Cao, Jinde ^{[1
,2
,3
]}

Alsaedi, Ahmad ^{[4
]}

Alsaadi, Fuad ^{[5
]}

机构：

[1] Southeast Univ, Sch Math, Nanjing 210096, Jiangsu, Peoples R China

[2] Southeast Univ, Res Ctr Complex Syst & Network Sci, Nanjing 210096, Jiangsu, Peoples R China

[3] King Abdulaziz Univ, Dept Math, Fac Sci, Jeddah 21589, Saudi Arabia

[4] King Abdulaziz Univ, Fac Sci, Nonlinear Anal & Appl Math NAAM Res Grp, Jeddah 21589, Saudi Arabia

[5] King Abdulaziz Univ, Dept Elect & Comp Engn, Fac Engn, Jeddah 21589, Saudi Arabia

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2017年 / 313卷

基金：

中国国家自然科学基金;

关键词：

Cohen-Grossberg neural network; Exponential synchronization; Fixed-time synchronization; Reaction-diffusion; ROBUST STABILITY; STRATEGIES; PASSIVITY;

D O I：

10.1016/j.amc.2017.05.073

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper is devoted to the global exponential and fixed-time synchronization of delayed reaction-diffusion Cohen-Grossberg neural networks. Adaptive controllers are designed such that the addressed system can realize global exponential synchronization goal under the framework of inequality techniques, Lyapunov method as well as some suitable assumptions. Furthermore, as corollaries, the corresponding conclusion is provided to ensure the delayed Cohen-Grossberg neural networks without reaction-diffusion term can reach fixed-time synchronization goal. In addition, the settling time of fixed-time synchronization can be adjusted to desired values regardless of initial conditions, which is more reasonable. Finally, two numerical examples and its simulations are given to show the effectiveness of the obtained results. (C) 2017 Elsevier Inc. All rights reserved.

引用

页码：37 / 51

页数：15

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