The effects of extreme multistability on the collective dynamics of coupled memristive neurons

被引:26
|
作者
Wang, Zhen [1 ,2 ]
Ramamoorthy, Ramesh [3 ]
Xi, Xiaojian [1 ]
Rajagopal, Karthikeyan [4 ]
Zhang, Peijun [1 ]
Jafari, Sajad [5 ,6 ]
机构
[1] Xijing Univ, Sch Sci, Xian Key Lab Adv Photo Elect Mat & Energy Convers, Xian 710123, Peoples R China
[2] Xijing Univ, Shaanxi Int Joint Res Ctr Appl Technol Controllab, Sch Sci, Xian 710123, Peoples R China
[3] Chennai Inst Technol, Ctr Artificial Intelligence, Chennai 600069, Tamil Nadu, India
[4] Chennai Inst Technol, Ctr Nonlinear Syst, Chennai 600069, Tamil Nadu, India
[5] Amirkabir Univ Technol, Hlth Technol Res Inst, Tehran Polytech, Tehran, Iran
[6] Amirkabir Univ Technol, Dept Biomed Engn, Tehran Polytech, Tehran, Iran
来源
EUROPEAN PHYSICAL JOURNAL-SPECIAL TOPICS | 2022年 / 231卷 / 16-17期
关键词
ELECTROMAGNETIC INDUCTION; CHIMERA STATES; MODEL; NETWORK; DELAY;
D O I
10.1140/epjs/s11734-022-00558-x
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The coexistence of different attractors, known as multistability, is an exciting phenomenon in the nonlinear dynamics field. Multistability has been widely studied in different dynamical systems; however, it has received less attention in coupled oscillators. This paper investigates coupled memristive Hindmarsh-Rose neurons, in which the memristor shows the effects of electromagnetic induction. The model has extreme multistability depending on the initial condition of the memristor. The collective behaviors of the network are considered by selecting different sets of initial conditions. The results represent the formation of different chimera, multi-headed chimera, and cluster synchronization patterns. The dynamics of neurons also rely on the coupling strength and may vary in time between the attractors. In periodic firing, the neurons can generate four clusters that have synchronous variations in different amplitudes.
引用
收藏
页码:3087 / 3094
页数:8
相关论文
共 50 条
  • [21] Hidden extreme multistability and synchronicity of memristor-coupled non-autonomous memristive Fitzhugh-Nagumo models
    Chen, Mo
    Luo, Xuefeng
    Suo, Yunhe
    Xu, Quan
    Wu, Huagan
    NONLINEAR DYNAMICS, 2023, 111 (08) : 7773 - 7788
  • [22] Self-organization collective dynamics of heterogeneous neurons with memristive and plastic chemical synapses
    Cheng, Xinhong
    Song, Xinlin
    Wang, Rong
    INTERNATIONAL JOURNAL OF MODERN PHYSICS B, 2022, 36 (03):
  • [23] Extreme multistability and amplitude modulation in memristive chaotic system and application to image encryption
    Qin, Ming-Hong
    Lai, Qiang
    OPTIK, 2023, 272
  • [24] Memristive Characteristics and Extreme Multistability of LLC DC-DC Resonant Converters
    Lu, Yimin
    Wei, Xuefei
    Huang, Xianfeng
    Yin, Zhihong
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2024, 71 (07) : 7020 - 7029
  • [25] Multiscroll Chaos and Extreme Multistability of Memristive Chaotic System with Application to Image Encryption
    Qiang Lai
    Yuan Liu
    Zhijie Chen
    Journal of Vibration Engineering & Technologies, 2024, 12 : 3487 - 3505
  • [26] Multiscroll Chaos and Extreme Multistability of Memristive Chaotic System with Application to Image Encryption
    Lai, Qiang
    Liu, Yuan
    Chen, Zhijie
    JOURNAL OF VIBRATION ENGINEERING & TECHNOLOGIES, 2024, 12 (03) : 3487 - 3505
  • [27] A Conservative Memristive Chaotic System with Extreme Multistability and Its Application in Image Encryption
    Li, Jian
    Liang, Bo
    Zhang, Xiefu
    Yu, Zhixin
    ENTROPY, 2023, 25 (12)
  • [28] Synchronous control of memristive hindmarsh-rose neuron models with extreme multistability
    Yan, Shaohui
    Wang, Jialong
    Song, Jincai
    INTEGRATION-THE VLSI JOURNAL, 2025, 100
  • [29] Hidden Dynamics, Multistability and Synchronization of a Memristive Hindmarsh-Rose Model
    Qiao, Shuai
    Gao, Chenghua
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 2022, 32 (16):
  • [30] A set of five generalised memristive synapses for the hidden nonlinear dynamics in three coupled neurons
    Singh, Jay Prakash
    CHAOS SOLITONS & FRACTALS, 2024, 188