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

页码：570 / 586

页数：17

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