Synchronization for fractional-order time-delayed memristor-based neural networks with parameter uncertainty

被引：82
|
作者：
Gu, Yajuan [1 ]
Yu, Yongguang [1 ]
Wang, Hu [2 ]
机构：
[1] Beijing Jiaotong Univ, Dept Math, Beijing 100044, Peoples R China
[2] Cent Univ Finance & Econ, Sch Stat & Math, Beijing 100081, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2016年 / 353卷 / 15期
关键词：
STABILITY ANALYSIS; PROJECTIVE SYNCHRONIZATION; DYNAMIC-ANALYSIS; DESIGN;
D O I：
10.1016/j.jfranklin.2016.06.029
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, the global synchronization for fractional-order multiple time-delayed memristor-based neural networks with parameter uncertainty is investigated. A comparison theorem for a class of fractional order multiple time-delayed systems is given. Under the framework of Filippov solution and differential inclusion theory, the synchronization conditions of fractional-order multiple time-delayed memristor-based neural networks with parameter uncertainty are derived, based on the given comparison theorem and Lyapunov method. Furthermore, the global asymptotical stability conditions of fractional-order multiple time-delayed memristor-based neural networks are obtained. Finally, two numerical examples are presented to show the effectiveness of our theoretical results. (C) 2016 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：3657 / 3684
页数：28
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