Stability and Hopf bifurcation analysis of fractional-order complex-valued neural networks with time delays

被引:0
|
作者
R Rakkiyappan
K Udhayakumar
G Velmurugan
Jinde Cao
Ahmed Alsaedi
机构
[1] Bharathiar University,Department of Mathematics
[2] Southeast University,School of Mathematics and Research Center for Complex Systems and Network Sciences
[3] King Abdulaziz University,Department of Mathematics, Faculty of Science
关键词
Hopfield neural networks; fractional-order; time delays; hub structure; ring structure; stability; Hopf bifurcation;
D O I
暂无
中图分类号
学科分类号
摘要
This paper considers a class of fractional-order complex-valued Hopfield neural networks (CVHNNs) with time delay for analyzing the dynamic behaviors such as local asymptotic stability and Hopf bifurcation. In the case of a neural network with hub and ring structure, the stability of the equilibrium state is investigated by analyzing the eigenvalue of the corresponding characteristic matrix for the hub and ring structured fractional-order time delay models using a Laplace transformation for the Caputo-fractional derivatives. Some sufficient conditions are established to guarantee the uniqueness of the equilibrium point. In addition, conditions for the occurrence of a Hopf bifurcation are also presented. Finally, numerical examples are given to demonstrate the effectiveness of the derived results.
引用
收藏
相关论文
共 50 条
  • [21] Existence and finite-time stability of discrete fractional-order complex-valued neural networks with time delays
    You, Xingxing
    Song, Qiankun
    Zhao, Zhenjiang
    NEURAL NETWORKS, 2020, 123 : 248 - 260
  • [22] Finite-time stability analysis of fractional-order complex-valued memristor-based neural networks with time delays
    Rakkiyappan, R.
    Velmurugan, G.
    Cao, Jinde
    NONLINEAR DYNAMICS, 2014, 78 (04) : 2823 - 2836
  • [23] Finite-time stability analysis of fractional-order complex-valued memristor-based neural networks with time delays
    R. Rakkiyappan
    G. Velmurugan
    Jinde Cao
    Nonlinear Dynamics, 2014, 78 : 2823 - 2836
  • [24] Stochastic stability of fractional-order Markovian jumping complex-valued neural networks with time-varying delays
    Aravind, R. Vijay
    Balasubramaniam, P.
    NEUROCOMPUTING, 2021, 439 : 122 - 133
  • [25] Global asymptotic stability of fractional-order complex-valued neural networks with probabilistic time-varying delays
    Chen, Sihan
    Song, Qiankun
    Zhao, Zhenjiang
    Liu, Yurong
    Alsaadi, Fuad E.
    NEUROCOMPUTING, 2021, 450 : 311 - 318
  • [26] Impact of leakage delay on bifurcation in fractional-order complex-valued neural networks
    Xu, Changjin
    Liao, Maoxin
    Li, Peiluan
    Yuan, Shuai
    CHAOS SOLITONS & FRACTALS, 2021, 142
  • [27] Synchronization in uncertain fractional-order memristive complex-valued neural networks with multiple time delays
    Zhang, Weiwei
    Zhang, Hai
    Cao, Jinde
    Alsaadi, Fuad E.
    Chen, Dingyuan
    NEURAL NETWORKS, 2019, 110 : 186 - 198
  • [28] Synchronization of Discrete-Time Fractional-Order Complex-Valued Neural Networks with Distributed Delays
    Perumal, R.
    Hymavathi, M.
    Ali, M. Syed
    Mahmoud, Batul A. A.
    Osman, Waleed M.
    Ibrahim, Tarek F.
    FRACTAL AND FRACTIONAL, 2023, 7 (06)
  • [29] Adaptive Synchronization of Fractional-Order Complex-Valued Neural Networks With Time-Varying Delays
    Hui, Meng
    Yao, Ning
    Iu, Herbert Ho-Ching
    Yao, Rui
    Bai, Lin
    IEEE ACCESS, 2022, 10 : 45677 - 45688
  • [30] Finite-time stability for fractional-order complex-valued neural networks with time delay
    Hu, Taotao
    He, Zheng
    Zhang, Xiaojun
    Zhong, Shouming
    APPLIED MATHEMATICS AND COMPUTATION, 2020, 365 (365)