Finite-time synchronization for memristor-based neural networks with time-varying delays

被引：164
|
作者：
Abdurahman, Abdujelil [1 ]
Jiang, Haijun [1 ]
Teng, Zhidong [1 ]
机构：
[1] Xinjiang Univ, Coll Math & Syst Sci, Urumqi 830046, Xinjiang, Peoples R China
来源：
NEURAL NETWORKS | 2015年 / 69卷
关键词：
Memristor; Finite-time synchronization; Neural network; Time-varying delay; EXPONENTIAL SYNCHRONIZATION; NONLINEAR-SYSTEMS; STABILIZATION;
D O I：
10.1016/j.neunet.2015.04.015
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor, which is an ideal tool to mimic the functionalities of the human brain. In this paper, finite-time synchronization is considered for a class of memristor-based neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, several new sufficient conditions ensuring the finite-time synchronization of memristor-based chaotic neural networks are obtained by using analysis technique, finite time stability theorem and adding a suitable feedback controller. Besides, the upper bounds of the settling time of synchronization are estimated. Finally, a numerical example is given to show the effectiveness and feasibility of the obtained results. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：20 / 28
页数：9
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