Finite-time synchronization of memristor-based complex-valued neural networks with time delays

被引：28
|
作者：
Sun, Kaili [1 ]
Zhu, Song [1 ]
Wei, Yongchang [2 ]
Zhang, Xiaoke [1 ]
Gao, Fei [1 ]
机构：
[1] China Univ Min & Technol, Sch Math, Xuzhou 221116, Jiangsu, Peoples R China
[2] Zhongnan Univ Econ & Law, Sch Business Adm, Wuhan 430073, Hubei, Peoples R China
来源：
PHYSICS LETTERS A | 2019年 / 383卷 / 19期
基金：
中国国家自然科学基金;
关键词：
Memristor; Finite-time synchronization; Complex-valued neural networks; Time delays; EXPONENTIAL STABILITY; DISCRETE; STABILIZATION; PERIODICITY; SYSTEMS;
D O I：
10.1016/j.physleta.2019.04.032
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
This paper deals with the problem of finite-time synchronization of memristor-based complex-valued neural networks (MCVNNs) with time delays. Based on the theory of differential inclusions with discontinuous right-hand side, we establish a new algebraic criterion of the finite-time synchronization of memristor-based complex-valued neural networks with time delays. The obtained theoretical results complement and improve some existing achievements in the real number field. Meanwhile, the obtained sufficient condition is conducive to qualitative analysis for some complex-valued nonlinear delayed systems. In the end, the conclusion is substantiated with an example of numerical simulation. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码：2255 / 2263
页数：9
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