Impulsive synchronization of stochastic reaction-diffusion neural networks with mixed time delays

被引：44
作者：
Sheng, Yin
Zeng, Zhigang [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Hubei, Peoples R China
来源：
NEURAL NETWORKS | 2018年 / 103卷
关键词：
Stochastic reaction-diffusion neural networks; Mixed time delays; Synchronization; Impulse; Stochastic analysis; DIRICHLET BOUNDARY-CONDITIONS; GLOBAL EXPONENTIAL STABILITY; VARYING DELAYS; DISTRIBUTED DELAYS; SAMPLED-DATA; INTERMITTENT CONTROL; CHAOTIC SYSTEMS; CONTROLLER;
D O I：
10.1016/j.neunet.2018.03.010
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper discusses impulsive synchronization of stochastic reaction-diffusion neural networks with Dirichlet boundary conditions and hybrid time delays. By virtue of inequality techniques, theories of stochastic analysis, linear matrix inequalities, and the contradiction method, sufficient criteria are proposed to ensure exponential synchronization of the addressed stochastic reaction-diffusion neural networks with mixed time delays via a designed impulsive controller. Compared with some recent studies, the neural network models herein are more general, some restrictions are relaxed, and the obtained conditions enhance and generalize some published ones. Finally, two numerical simulations are performed to substantiate the validity and merits of the developed theoretical analysis. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码：83 / 93
页数：11
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