Multisynchronization of a class of delayed memristor-based neural networks

被引：0
|
作者：
Lin, Ya-Qi [1 ,2 ]
Ge, Ming-Feng [3 ]
Ding, Teng-Fei [3 ]
Zhu, Ziqi [1 ,2 ]
He, Juanjuan [1 ,2 ]
机构：
[1] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430081, Peoples R China
[2] Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan 430081, Peoples R China
[3] China Univ Geosci, Sch Mech Engn & Elect Informat, Wuhan 430074, Peoples R China
来源：
PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC) | 2019年
基金：
中国国家自然科学基金;
关键词：
Delayed memristor-based neural networks; Multisynchronization; Multiple agreement systems; Feedback controller; QUASI-SYNCHRONIZATION; CONSENSUS; SYSTEMS; DISSIPATIVITY;
D O I：
10.23919/chicc.2019.8866412
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 the multisynchronization problem of a new class of delayed memristor-based neural networks (DMNNs). To address this problem, a class of feedback controller is designed. By employing the Lyapunov stability theory, the corresponding sufficient conditions for achieving multisynchronization of DMNNs with the presented feedback control are derived. It implies that multiple agreements of system responses are obtained via the dynamical evolution of the controlled DMNNs. Finally, a simulation experiment is presented to verify the validity and feasibility of the main result of the DMNNs.
引用
收藏
页码：5509 / 5513
页数：5
相关论文
共 50 条
  • [1] Multisynchronization of Interconnected Memristor-Based Impulsive Neural Networks With Fuzzy Hybrid Control
    Hu, Bin
    Guan, Zhi-Hong
    Yu, Xinghuo
    Luo, Qingming
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2018, 26 (05) : 3069 - 3084
  • [2] Pinning multisynchronization of delayed fractional-order memristor-based neural networks with nonlinear coupling and almost-periodic perturbations
    Peng, Libiao
    Li, Xifeng
    Bi, Dongjie
    Xie, Xuan
    Xie, Yongle
    [J]. NEURAL NETWORKS, 2021, 144 : 372 - 383
  • [3] Adaptive Synchronization for Delayed Chaotic Memristor-Based Neural Networks
    Xin, Youming
    Cheng, Zunshui
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (02) : 601 - 610
  • [4] Memristor-based neural networks
    Thomas, Andy
    [J]. JOURNAL OF PHYSICS D-APPLIED PHYSICS, 2013, 46 (09)
  • [5] Synchronization control of a class of memristor-based recurrent neural networks
    Wu, Ailong
    Wen, Shiping
    Zeng, Zhigang
    [J]. INFORMATION SCIENCES, 2012, 183 (01) : 106 - 116
  • [6] Global exponential almost periodicity of a delayed memristor-based neural networks
    Chen, Jiejie
    Zeng, Zhigang
    Jiang, Ping
    [J]. NEURAL NETWORKS, 2014, 60 : 33 - 43
  • [7] Advances in Memristor-Based Neural Networks
    Xu, Weilin
    Wang, Jingjuan
    Yan, Xiaobing
    [J]. FRONTIERS IN NANOTECHNOLOGY, 2021, 3
  • [8] Passivity analysis of delayed reaction-diffusion memristor-based neural networks
    Cao, Yanyi
    Cao, Yuting
    Wen, Shiping
    Huang, Tingwen
    Zeng, Zhigang
    [J]. NEURAL NETWORKS, 2019, 109 : 159 - 167
  • [9] Finite-time synchronization criteria for delayed memristor-based neural networks
    Li, Ning
    Cao, Jinde
    Xiao, Huimin
    [J]. PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 3590 - 3594
  • [10] Finite-time synchronization of stochastic memristor-based delayed neural networks
    Shi, Yanchao
    Zhu, Peiyong
    [J]. NEURAL COMPUTING & APPLICATIONS, 2018, 29 (06): : 293 - 301
12345