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

被引：40
|
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 50 条
  • [1] Projective synchronization for fractional-order memristor-based neural networks with time delays
    Yajuan Gu
    Yongguang Yu
    Hu Wang
    [J]. Neural Computing and Applications, 2019, 31 : 6039 - 6054
  • [2] Hybrid projective synchronization of fractional-order memristor-based neural networks with time delays
    Velmurugan, G.
    Rakkiyappan, R.
    [J]. NONLINEAR DYNAMICS, 2016, 83 (1-2) : 419 - 432
  • [3] Hybrid projective synchronization of fractional-order memristor-based neural networks with time delays
    G. Velmurugan
    R. Rakkiyappan
    [J]. Nonlinear Dynamics, 2016, 83 : 419 - 432
  • [4] Projective synchronization of fractional-order memristor-based neural networks
    Bao, Hai-Bo
    Cao, Jin-De
    [J]. NEURAL NETWORKS, 2015, 63 : 1 - 9
  • [5] Finite-time synchronization of fractional-order memristor-based neural networks with time delays
    Velmurugan, G.
    Rakkiyappan, R.
    Cao, Jinde
    [J]. NEURAL NETWORKS, 2016, 73 : 36 - 46
  • [6] Finite-time projective synchronization of memristor-based delay fractional-order neural networks
    Zheng, Mingwen
    Li, Lixiang
    Peng, Haipeng
    Xiao, Jinghua
    Yang, Yixian
    Zhao, Hui
    [J]. NONLINEAR DYNAMICS, 2017, 89 (04) : 2641 - 2655
  • [7] Finite-time projective synchronization of memristor-based delay fractional-order neural networks
    Mingwen Zheng
    Lixiang Li
    Haipeng Peng
    Jinghua Xiao
    Yixian Yang
    Hui Zhao
    [J]. Nonlinear Dynamics, 2017, 89 : 2641 - 2655
  • [8] Adaptive Synchronization of Fractional-Order Memristor-Based Neural Networks with Multiple Time-Varying Delays
    Jia, Jia
    Huang, Xia
    Li, Yuxia
    Wang, Zhen
    [J]. 2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 1229 - 1234
  • [9] Adaptive synchronization of fractional-order memristor-based neural networks with time delay
    Haibo Bao
    Ju H. Park
    Jinde Cao
    [J]. Nonlinear Dynamics, 2015, 82 : 1343 - 1354
  • [10] Adaptive synchronization of fractional-order memristor-based neural networks with time delay
    Bao, Haibo
    Park, Ju H.
    Cao, Jinde
    [J]. NONLINEAR DYNAMICS, 2015, 82 (03) : 1343 - 1354
12345