Exponential synchronization for reaction-diffusion networks with mixed delays in terms of p-norm via intermittent driving

被引：77

作者：

Hu, Cheng ^{[1
]}

Yu, Juan ^{[1
]}

Jiang, Haijun ^{[1
]}

Teng, Zhidong ^{[1
]}

机构：

[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China

来源：

NEURAL NETWORKS | 2012年 / 31卷

关键词：

Exponential synchronization; Finite distributed delays; Intermittent control; Reaction-diffusion neural networks; Diffusion effects; DIRICHLET BOUNDARY-CONDITIONS; CHAOTIC NEURAL-NETWORKS; TIME-VARYING DELAYS; DISTRIBUTED DELAYS; ADAPTIVE SYNCHRONIZATION; IMAGE SEGMENTATION; STABILITY ANALYSIS; RECOGNITION; BINDING; SYSTEMS;

D O I：

10.1016/j.neunet.2012.02.038

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, the globally exponential synchronization for a class of reaction-diffusion neural networks with Dirichlet boundary conditions and mixed delays is investigated based on periodically intermittent control. Some new and useful synchronization criteria in terms of p-norm are derived by introducing multi-parameters, using Lyapunov functional theory. Subsequently, a feasible region of the control parameters for each neuron is derived for the realization of exponential synchronization. Besides, according to the theoretical results, the influences of diffusion strengths and diffusion spaces on synchronization are analyzed and a very interesting fact is revealed that the synchronization of neural networks with reaction-diffusions is more easily realized than those of neural networks without reaction-diffusions. Finally, a reaction-diffusion chaotic network is given to demonstrate the effectiveness of the proposed control methods. (C) 2012 Elsevier Ltd. All rights reserved.

引用

页码：1 / 11

页数：11

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