IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v172y2023ics0960077923004708.html
   My bibliography  Save this article

Stability of Hopfield neural network with resistive and magnetic coupling

Author

Listed:
  • Wu, Fuqiang
  • Kang, Ting
  • Shao, Yan
  • Wang, Qingyun

Abstract

Inspired by the interplay between both electrical and chemical synapses, we propose an analog electronic synapse-like model to characterize biological synaptic properties. By introducing the resistive and magnetic coupling, we consider hierarchical interconnection and the mixed couplings with two different kinds of coupling mechanisms. Meanwhile, based on Lyapunov function of the variable gradient method, stability of the Hopfield neural network with resistive and magnetic couplings was derived as the interconnection is symmetric and asymmetric, respectively. Furthermore, corresponding examples are calculated by using the numerical approach. The obtained results can be helpful to further develop brain-like systems based on the hierarchical Hopfield neural network with timing-dependent synaptic plasticity.

Suggested Citation

  • Wu, Fuqiang & Kang, Ting & Shao, Yan & Wang, Qingyun, 2023. "Stability of Hopfield neural network with resistive and magnetic coupling," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    • Handle: RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004708
    DOI: 10.1016/j.chaos.2023.113569
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923004708
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113569?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ren, Guodong & Xue, Yuxiong & Li, Yuwei & Ma, Jun, 2019. "Field coupling benefits signal exchange between Colpitts systems," Applied Mathematics and Computation, Elsevier, vol. 342(C), pages 45-54.
    2. Wang, Qingyun & Duan, Zhisheng & Chen, Guanrong & Feng, Zhaosheng, 2008. "Synchronization in a class of weighted complex networks with coupling delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(22), pages 5616-5622.
    3. Yao, Zhao & Wang, Chunni, 2021. "Control the collective behaviors in a functional neural network," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    4. S. Bianchi & I. Muñoz-Martin & E. Covi & A. Bricalli & G. Piccolboni & A. Regev & G. Molas & J. F. Nodin & F. Andrieu & D. Ielmini, 2023. "A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    5. Ge, Mengyan & Jia, Ya & Xu, Ying & Lu, Lulu & Wang, Huiwen & Zhao, Yunjie, 2019. "Wave propagation and synchronization induced by chemical autapse in chain Hindmarsh–Rose neural network," Applied Mathematics and Computation, Elsevier, vol. 352(C), pages 136-145.
    6. Klinshov, Vladimir V. & Kovalchuk, Andrey V. & Franović, Igor & Perc, Matjaž & Svetec, Milan, 2022. "Rate chaos and memory lifetime in spiking neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    7. Wu, Fuqiang & Ma, Jun & Zhang, Ge, 2019. "A new neuron model under electromagnetic field," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 590-599.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shao, Yan & Wu, Fuqiang & Wang, Qingyun, 2024. "Dynamics and stability of neural systems with indirect interactions involved energy levels," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guo, Yeye & Wang, Chunni & Yao, Zhao & Xu, Ying, 2022. "Desynchronization of thermosensitive neurons by using energy pumping," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 602(C).
    2. Wu, Fuqiang & Guo, Yitong & Ma, Jun & Jin, Wuyin, 2023. "Synchronization of bursting memristive Josephson junctions via resistive and magnetic coupling," Applied Mathematics and Computation, Elsevier, vol. 455(C).
    3. Hou, Zhangliang & Ma, Jun & Zhan, Xuan & Yang, Lijian & Jia, Ya, 2021. "Estimate the electrical activity in a neuron under depolarization field," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. Fossi, Jules Tagne & Njitacke, Zeric Tabekoueng & Tankeu, William Nguimeya & Mendimi, Joseph Marie & Awrejcewicz, Jan & Atangana, Jacques, 2023. "Phase synchronization and coexisting attractors in a model of three different neurons coupled via hybrid synapses," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    5. Yu, Dong & Wang, Guowei & Ding, Qianming & Li, Tianyu & Jia, Ya, 2022. "Effects of bounded noise and time delay on signal transmission in excitable neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Peng Chen & Fenghao Liu & Peng Lin & Peihong Li & Yu Xiao & Bihua Zhang & Gang Pan, 2023. "Open-loop analog programmable electrochemical memory array," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    7. Wafo Tekam, Raoul Blaise & Kengne, Jacques & Djuidje Kenmoe, Germaine, 2019. "High frequency Colpitts’ oscillator: A simple configuration for chaos generation," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 351-360.
    8. Yu, Dong & Wu, Yong & Yang, Lijian & Zhao, Yunjie & Jia, Ya, 2023. "Effect of topology on delay-induced multiple resonances in locally driven systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    9. Salari, Nasir, 2022. "Electric vehicles adoption behaviour: Synthesising the technology readiness index with environmentalism values and instrumental attributes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 164(C), pages 60-81.
    10. Rajagopal, Karthikeyan & Hussain, Iqtadar & Rostami, Zahra & Li, Chunbiao & Pham, Viet-Thanh & Jafari, Sajad, 2021. "Magnetic induction can control the effect of external electrical stimuli on the spiral wave," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    11. Li, Fan, 2020. "Effect of field coupling on the wave propagation in the neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    12. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    13. Lu, Lulu & Ge, Mengyan & Xu, Ying & Jia, Ya, 2019. "Phase synchronization and mode transition induced by multiple time delays and noises in coupled FitzHugh–Nagumo model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    14. Anton, Sorin Gabriel, 2021. "The impact of temperature increase on firm profitability. Empirical evidence from the European energy and gas sectors," Applied Energy, Elsevier, vol. 295(C).
    15. Wang, Zhizhi & Hu, Bing & Zhou, Weiting & Xu, Minbo & Wang, Dingjiang, 2023. "Hopf bifurcation mechanism analysis in an improved cortex-basal ganglia network with distributed delays: An application to Parkinson’s disease," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    16. Akhmet, Marat & Başkan, Kağan & Yeşil, Cihan, 2024. "Markovian noise-induced delta synchronization approach for Hindmarsh–Rose model," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    17. Alberto Boretti & Stefania Castelletto, 2021. "Techno-economic performances of future concentrating solar power plants in Australia," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
    18. Rajagopal, Karthikeyan & Jafari, Sajad & Li, Chunbiao & Karthikeyan, Anitha & Duraisamy, Prakash, 2021. "Suppressing spiral waves in a lattice array of coupled neurons using delayed asymmetric synapse coupling," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    19. Zhang, Yan-Jie & Liu, Song & Yang, Ran & Tan, Ying-Ying & Li, Xiaoyan, 2019. "Global synchronization of fractional coupled networks with discrete and distributed delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 830-837.
    20. Ge, Mengyan & Lu, Lulu & Xu, Ying & Mamatimin, Rozihajim & Pei, Qiming & Jia, Ya, 2020. "Vibrational mono-/bi-resonance and wave propagation in FitzHugh–Nagumo neural systems under electromagnetic induction," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:172:y:2023:i:c:s0960077923004708. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.