On synchronization for chaotic memristor-based neural networks with time-varying delays

被引：7
|
作者：
Zheng, Cheng-De [1 ]
Xian, Yongjin [1 ]
机构：
[1] Dalian Jiaotong Univ, Dept Math, Dalian 116028, Peoples R China
来源：
NEUROCOMPUTING | 2016年 / 216卷
基金：
中国国家自然科学基金;
关键词：
Memristive neural networks; Synchronization; Wirtinger-based integral inequality; Reciprocally convex combination; Free-matrix-based inequality; EXPONENTIAL SYNCHRONIZATION; INTEGRAL INEQUALITY; STABILITY ANALYSIS; PASSIVITY ANALYSIS; IMPULSIVE CONTROL; MULTIPLE DELAYS; SYSTEMS; DISCRETE; DISSIPATIVITY; CRITERIA;
D O I：
10.1016/j.neucom.2016.08.028
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 synchronization problem for chaotic memristor-based neural networks with time-varying delays. First, a novel lemma is proposed to deal with the switching jump parameters. Then, a novel inequality is established which is a multiple integral form of the Wirtinger-based integral inequality. Next, by applying the reciprocally convex combination approach, linear convex combination technique, auxiliary function-based integral inequalities and a free-matrix-based inequality, several novel delay-dependent conditions are established to achieve the globally asymptotical synchronization for the chaotic memristor-based neural networks. Finally, a numerical example is provided to demonstrate the effectiveness of the theoretical results. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码：570 / 586
页数：17
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