New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay

被引：77
|
作者：
Du, Feifei [1 ,2 ]
Lu, Jun-Guo [1 ,2 ]
机构：
[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China
[2] Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2021年 / 389卷
基金：
中国国家自然科学基金;
关键词：
Fractional order neural networks; Finite-time synchronization; Time delay; Memristor; GRONWALL INEQUALITY; PROJECTIVE SYNCHRONIZATION; GLOBAL SYNCHRONIZATION; INTEGRAL-INEQUALITIES; LAG SYNCHRONIZATION; COMPLEX NETWORKS; STABILITY; SYSTEMS;
D O I：
10.1016/j.amc.2020.125616
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
A new fractional order Gronwall inequality with time delay is developed in this paper. Based on this inequality, a new criterion for finite-time synchronization of fractional order memristor-based neural networks (FMNNs) with time delay is derived. In addition, two numerical examples are exhibited to illustrate the effectiveness of the obtained results. (C) 2020 Elsevier Inc. All rights reserved.
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页数：16
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