Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control

被引：215
作者：
Zhang, Guodong
Shen, Yi [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Sch Automat, Wuhan 430074, Peoples R China
来源：
NEURAL NETWORKS | 2014年 / 55卷
基金：
美国国家科学基金会; 中国国家自然科学基金;
关键词：
Chaotic dynamical systems; Exponential synchronization; Memristor; Time-varying delays; Intermittent control; TIME-VARYING DELAYS; MIXED DELAYS; STABILIZATION; OSCILLATOR; BEHAVIORS; STABILITY; FEEDBACK; CIRCUIT; SYSTEMS;
D O I：
10.1016/j.neunet.2014.03.009
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 investigates the exponential synchronization of coupled memristor-based chaotic neural networks with both time-varying delays and general activation functions. And here, we adopt nonsmooth analysis and control theory to handle memristor-based chaotic neural networks with discontinuous right-hand side. In particular, several new criteria ensuring exponential synchronization of two memristor-based chaotic neural networks are obtained via periodically intermittent control. In addition, the new proposed results here are very easy to verify and also complement, extend the earlier publications. Numerical simulations on the chaotic systems are presented to illustrate the effectiveness of the theoretical results. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码：1 / 10
页数：10
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