Pinning synchronization of fractional-order memristor-based neural networks with multiple time-varying delays via static or dynamic coupling

被引：23

作者：

Jia, Jia ^{[1
,2
]}

Zeng, Zhigang ^{[1
]}

Wang, Fei ^{[3
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Artificial Intelligence & Automat, Key Lab Image Proc & Intelligent Control, Wuhan 430074, Peoples R China

[2] Shandong Univ, Sch Control Sci & Engn, Jinan 250061, Peoples R China

[3] Qufu Normal Univ, Sch Math Sci, Qufu 273165, Shandong, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE | 2021年 / 358卷 / 01期

基金：

中国国家自然科学基金;

关键词：

QUASI-SYNCHRONIZATION; STABILITY; CRITERIA; CHAOS;

D O I：

10.1016/j.jfranklin.2020.09.028

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper investigates global asymptotical synchronization between fractional-order memristor-based neural networks (FMNNs) with multiple time-varying delays (MTDs) by pinning control. Two classes of coupling manners, static manner and dynamic manner, are introduced into the pinning controller respectively. For the case of static coupling, to make the controller exclude fraction, 1-norm Lyapunov function and fractional Halanay inequality in MTDs case are utilized for synthesis of controller and convergence analysis of synchronization error. For the case of dynamic coupling, a fractional differential inequality is proved and discussed in an elaborate way, and then global asymptotical synchronization is analyzed by means of Lyapunov-like function and the newly-proved inequality. Lastly, numerical simulations are carried out to show the practicability of the pinning controllers and the feasibility of the obtained synchronization criteria. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：895 / 933

页数：39

共 52 条

[1] Lyapunov functions for fractional order systems [J].

Aguila-Camacho, Norelys ;

Duarte-Mermoud, Manuel A. ;

Gallegos, Javier A. .

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2014, 19 (09) :2951-2957

[2] Chaotic behavior in noninteger-order cellular neural networks [J].

Arena, P ;

Fortuna, L ;

Porto, D .

PHYSICAL REVIEW E, 2000, 61 (01) :776-781

[3] Bifurcation and chaos in noninteger order cellular neural networks [J].

Arena, P ;

Caponetto, R ;

Fortuna, L ;

Porto, D .

INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 1998, 8 (07) :1527-1539

[4]

Aubin J., 1984, Differential inclusions, set-valued maps and viability theory

[5] Projective synchronization of fractional-order memristor-based neural networks [J].

Bao, Hai-Bo ;

Cao, Jin-De .

NEURAL NETWORKS, 2015, 63 :1-9

[6] Non-fragile state estimation for fractional-order delayed memristive BAM neural networks [J].

Bao, Haibo ;

Park, Ju H. ;

Cao, Jinde .

NEURAL NETWORKS, 2019, 119 :190-199

[7] Adaptive synchronization of fractional-order memristor-based neural networks with time delay [J].

Bao, Haibo ;

Park, Ju H. ;

Cao, Jinde .

NONLINEAR DYNAMICS, 2015, 82 (03) :1343-1354

[8]

Boroomand A, 2009, LECT NOTES COMPUT SC, V5506, P883, DOI 10.1007/978-3-642-02490-0_108

[9]

Bridger Mark., 2007, Real Analysis: A Constructive Approach

[10] O(t-α)-synchronization and Mittag-Leffler synchronization for the fractional-order memristive neural networks with delays and discontinuous neuron activations [J].

Chen, Jiejie ;

Chen, Boshan ;

Zeng, Zhigang .

NEURAL NETWORKS, 2018, 100 :10-24

← 1 2 3 4 5 6 →