Exponential stability and synchronization of Memristor-based fractional-order fuzzy cellular neural networks with multiple delays

被引:35
|
作者
Yao, Xueqi [1 ,2 ]
Liu, Xinzhi [2 ]
Zhong, Shouming [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China
[2] Univ Waterloo, Dept Appl Math, Waterloo, ON N2L 3G1, Canada
关键词
Fuzzy cellular neural networks; Fractional-order; Memristor; Multiple delays; Exponential stability; FINITE-TIME STABILITY; NONLINEAR-SYSTEMS;
D O I
10.1016/j.neucom.2020.08.057
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The stability and synchronization problems are addressed in this study for the memristor-based fractional-order fuzzy cellular neural networks with multiple delays. By using the Laplace transform method, fractional-order calculus approach and the method of complex function, three exponential sta-bility criteria are derived. Compared with the existing results of the above system, the novel exponentially stable and synchronization conditions are first proposed. The obtained results can be applied not only to fractional-order systems, but also to integer-order systems. A two-dimension example and a three-dimension example and a practical example are given to illustrate the validity and merits. (c) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:239 / 250
页数:12
相关论文
共 50 条
  • [1] Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks
    Zheng, Mingwen
    Li, Lixiang
    Peng, Haipeng
    Xiao, Jinghua
    Yang, Yixian
    Zhang, Yanping
    Zhao, Hui
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2018, 59 : 272 - 291
  • [2] Stability and synchronization of memristor-based fractional-order delayed neural networks
    Chen, Liping
    Wu, Ranchao
    Cao, Jinde
    Liu, Jia-Bao
    NEURAL NETWORKS, 2015, 71 : 37 - 44
  • [3] Projective synchronization for fractional-order memristor-based neural networks with time delays
    Yajuan Gu
    Yongguang Yu
    Hu Wang
    Neural Computing and Applications, 2019, 31 : 6039 - 6054
  • [4] Projective synchronization for fractional-order memristor-based neural networks with time delays
    Gu, Yajuan
    Yu, Yongguang
    Wang, Hu
    NEURAL COMPUTING & APPLICATIONS, 2019, 31 (10): : 6039 - 6054
  • [5] Adaptive Synchronization of Fractional-Order Memristor-Based Neural Networks with Multiple Time-Varying Delays
    Jia, Jia
    Huang, Xia
    Li, Yuxia
    Wang, Zhen
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 1229 - 1234
  • [6] Hybrid projective synchronization of fractional-order memristor-based neural networks with time delays
    Velmurugan, G.
    Rakkiyappan, R.
    NONLINEAR DYNAMICS, 2016, 83 (1-2) : 419 - 432
  • [7] Hybrid projective synchronization of fractional-order memristor-based neural networks with time delays
    G. Velmurugan
    R. Rakkiyappan
    Nonlinear Dynamics, 2016, 83 : 419 - 432
  • [8] Fixed-Time Synchronization of Delayed Fractional-Order Memristor-Based Fuzzy Cellular Neural Networks
    Sun, Yeguo
    Liu, Yihong
    IEEE ACCESS, 2020, 8 : 165951 - 165962
  • [9] Projective synchronization of fractional-order memristor-based neural networks
    Bao, Hai-Bo
    Cao, Jin-De
    NEURAL NETWORKS, 2015, 63 : 1 - 9
  • [10] Finite-time synchronization for fractional-order memristor-based neural networks with discontinuous activations and multiple delays
    Ding, Dawei
    You, Ziruo
    Hu, Yongbing
    Yang, Zongli
    Ding, Lianghui
    MODERN PHYSICS LETTERS B, 2020, 34 (15):