Passivity of fractional-order coupled neural networks with multiple state/derivative couplings

被引：26
|
作者：
Liu, Chen-Guang [1 ]
Wang, Jin-Liang [1 ,2 ]
机构：
[1] Tiangong Univ, Sch Comp Sci & Technol, Tianjin Key Lab Autonomous Intelligence Technol &, Tianjin 300387, Peoples R China
[2] Linyi Univ, Sch Informat Sci & Technol, Linyi 276005, Shandong, Peoples R China
来源：
NEUROCOMPUTING | 2021年 / 455卷
基金：
中国国家自然科学基金;
关键词：
Fractional-order coupled neural networks; (FOCNNs); Multiple derivative couplings; Multiple state couplings; Passivity; Synchronization; PINNING SYNCHRONIZATION; STABILITY ANALYSIS;
D O I：
10.1016/j.neucom.2021.05.050
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper respectively discusses the passivity of fractional-order coupled neural networks with multiple state couplings (FOCNNMSCs) or multiple derivative couplings (FOCNNMDCs). In light of fractional-order system theory, several sufficient conditions for ensuring the passivity of the FOCNNMSCs are established. Moreover, a synchronization criterion for the FOCNNMSCs is obtained under the condition that the FOCNNMSCs is output-strictly passive. Similarly, we also investigate the passivity of the FOCNNMDCs by resorting to the Lyapunov functional method, and the output-strict passivity is used to deal with the synchronization for the FOCNNMDCs. Finally, the effectiveness of the obtained criteria is verified by two numerical examples with simulations. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码：379 / 389
页数：11
相关论文
共 50 条
  • [41] Stability and synchronization of fractional-order memristive neural networks with multiple delays
    Chen, Liping
    Cao, Jinde
    Wu, Ranchao
    Tenreiro Machado, J. A.
    Lopes, Antonio M.
    Yang, Hejun
    NEURAL NETWORKS, 2017, 94 : 76 - 85
  • [42] Event-Triggered State Estimation for Fractional-Order Neural Networks
    Xu, Bingrui
    Li, Bing
    MATHEMATICS, 2022, 10 (03)
  • [43] Multisynchronization for Coupled Multistable Fractional-Order Neural Networks via Impulsive Control
    Zhang, Jin-E
    COMPLEXITY, 2017,
  • [44] Stabilization of fractional-order coupled systems with time delay on networks
    Chen, Liping
    Wu, Ranchao
    Chu, Zhaobi
    He, Yigang
    NONLINEAR DYNAMICS, 2017, 88 (01) : 521 - 528
  • [45] Synchronization of fractional-order memristive neural networks with time delays
    Chen, Chong
    Ding, Zhixia
    Li, Sai
    Wang, Liheng
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 2754 - 2759
  • [46] Dynamic analysis of a class of fractional-order neural networks with delay
    Chen, Liping
    Chai, Yi
    Wu, Ranchao
    Ma, Tiedong
    Zhai, Houzhen
    NEUROCOMPUTING, 2013, 111 : 190 - 194
  • [47] Passivity Analysis of Fractional-Order Neural Networks with Time-Varying Delay Based on LMI Approach
    Sau, Nguyen Huu
    Thuan, Mai Viet
    Huyen, Nguyen Thi Thanh
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2020, 39 (12) : 5906 - 5925
  • [48] Bifurcations in a fractional-order neural network with multiple leakage delays
    Huang, Chengdai
    Liu, Heng
    Shi, Xiangyun
    Chen, Xiaoping
    Xiao, Min
    Wang, Zhengxin
    Cao, Jinde
    NEURAL NETWORKS, 2020, 131 : 115 - 126
  • [49] Multiple Mittag-Leffler Stability of Fractional-Order Recurrent Neural Networks
    Liu, Peng
    Zeng, Zhigang
    Wang, Jun
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 47 (08): : 2279 - 2288
  • [50] Asymptotical stability for fractional-order Hopfield neural networks with multiple time delays
    Yao, Zichen
    Yang, Zhanwen
    Fu, Yongqiang
    Li, Jiachen
    MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2022, 45 (16) : 10052 - 10069
12345