Synchronization of neural networks with stochastic perturbation via aperiodically intermittent control

被引：94
作者：
Zhang, Wei [1 ]
Li, Chuandong [1 ]
Huang, Tingwen [2 ]
Xiao, Mingqing [3 ]
机构：
[1] Chongqing Univ, Coll Comp Sci, Chongqing 400044, Peoples R China
[2] Texas A&M Univ Qatar, Dept Math, Doha, Qatar
[3] So Illinois Univ, Dept Math, Carbondale, IL 62901 USA
来源：
NEURAL NETWORKS | 2015年 / 71卷
基金：
美国国家科学基金会;
关键词：
Synchronization; Neural networks; Stochastic perturbation; Aperiodically intermittent control; Adaptive control; TIME-VARYING DELAYS; EXPONENTIAL SYNCHRONIZATION; PERIODIC-SOLUTIONS; COMPLEX NETWORKS; STABILITY; STABILIZATION; DESIGN;
D O I：
10.1016/j.neunet.2015.08.002
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 synchronization problem for neural networks with stochastic perturbation is studied with intermittent control via adaptive aperiodicity. Under the framework of stochastic theory and Lyapunov stability method, we develop some techniques of intermittent control with adaptive aperiodicity to achieve the synchronization of a class of neural networks, modeled by stochastic systems. Some effective sufficient conditions are established for the realization of synchronization of the underlying network. Numerical simulations of two examples are provided to illustrate the theoretical results obtained in the paper. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：105 / 111
页数：7
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