Periodic synchronization in delayed memristive neural networks based on Filippov systems

被引：22

作者：

Cai, Zuowei ^{[1
]}

Huang, Lihong ^{[1
,2
]}

Wang, Dongshu ^{[2
,3
]}

Zhang, Lingling ^{[1
]}

机构：

[1] Hunan Womens Univ, Dept Informat Technol, Changsha 410002, Hunan, Peoples R China

[2] Hunan Univ, Coll Math & Econometr, Changsha 410082, Hunan, Peoples R China

[3] Huaqiao Univ, Sch Math Sci, Quanzhou 362021, Fujian, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2015年 / 352卷 / 10期

基金：

中国国家自然科学基金;

关键词：

EXPONENTIAL SYNCHRONIZATION; DIFFERENTIAL-INCLUSIONS; DYNAMIC-BEHAVIORS; DISSIPATIVITY; STABILITY; PASSIVITY; THEOREM;

D O I：

10.1016/j.jfranklin.2015.07.014

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we consider the possibility to implement the periodic synchronization control of memristive neural networks with time-varying delay. On the one hand, we apply a new method based on Kakutani's fixed point theorem of set-valued maps to obtain the existence of periodic solutions for memristive neural networks. On the other hand, by designing novel discontinuous state-feedback controller and introducing some new analytic techniques, the drive response structure of memristor-based neural networks with periodic coefficients can realize the p-type exponential complete synchronization. Moreover, the estimated rate of exponential synchronization depends on the time delay and system parameters. The analysis in this paper is performed via functional differential inclusions following the Filippov theory. Finally, the proposed design method and theoretical results are verified by numerical example with MATLAB programming. (C) 2015 The Franldin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：4638 / 4663

页数：26

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