Projective synchronization for fractional-order memristor-based neural networks with time delays

被引：46
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：
NEURAL COMPUTING & APPLICATIONS | 2019年 / 31卷 / 10期
基金：
中国国家自然科学基金;
关键词：
Memristor-based neural networks; Synchronization; Fractional-order; Time delays; STABILITY ANALYSIS; EXPONENTIAL SYNCHRONIZATION; ADAPTIVE-CONTROL; CHAOTIC SYSTEM; DYNAMICS; DESIGN;
D O I：
10.1007/s00521-018-3391-7
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, the global projective synchronization for fractional-order memristor-based neural networks with multiple time delays is investigated via combining open loop control with the time-delayed feedback control. A comparison theorem for a class of fractional-order systems with multiple time delays is proposed. Based on the given comparison theorem and Lyapunov method, the synchronization conditions are derived under the framework of Filippov solution and differential inclusion theory. Several feedback control strategies are given to ensure the realization of complete synchronization, anti-synchronization and the stabilization for the fractional-order memristor-based neural networks with time delays. Finally, a numerical example is given to illustrate the effectiveness of the theoretical results.
引用
收藏
页码：6039 / 6054
页数：16
相关论文
共 45 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]   Memristors: Pass or Fail? [J].
Anthes, Gary .
COMMUNICATIONS OF THE ACM, 2011, 54 (03) :22-24
[3]  
Aubin J.P., 1990, Set-Valued Analysis, DOI 10.1007/978-0-8176-4848-0
[4]   Projective synchronization of fractional-order memristor-based neural networks [J].
Bao, Hai-Bo ;
Cao, Jin-De .
NEURAL NETWORKS, 2015, 63 :1-9
[5]   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
[6]   Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay [J].
Bao, Haibo ;
Park, Ju H. ;
Cao, Jinde .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (01) :190-201
[7]  
Bhalekar S., 2011, J. Fract. Calc. Appl., V1, P1, DOI DOI 10.1155/2011/250763
[8]   Chaos-based M-ary digital communication technique using controlled projective synchronisation [J].
Chee, C. Y. ;
Xu, D. .
IEE PROCEEDINGS-CIRCUITS DEVICES AND SYSTEMS, 2006, 153 (04) :357-360
[9]   Global Mittag-Leffler stability and synchronization of memristor-based fractional-order neural networks [J].
Chen, Jiejie ;
Zeng, Zhigang ;
Jiang, Ping .
NEURAL NETWORKS, 2014, 51 :1-8
[10]   Dynamic analysis of a class of fractional-order neural networks with delay [J].
Chen, Liping ;
Chai, Yi ;
Wu, Ranchao ;
Ma, Tiedong ;
Zhai, Houzhen .
NEUROCOMPUTING, 2013, 111 :190-194
12345