IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v188y2024ics0960077924010300.html
   My bibliography  Save this article

Design and analysis of grid attractors in memristive Hopfield neural networks

Author

Listed:
  • Yuan, Fang
  • Qi, Yaning
  • Yu, Xiangcheng
  • Deng, Yue

Abstract

This paper proposes three types of memristive Hopfield neural networks (M-HNNs) that incorporate connections comprising memristor self-synapses and unidirectional synapses. The M-HNNs are designed as simple three-neuron structures capable of configuring multi-double-scroll attractors in terms of both attractor directions and numbers by applying an external excitation current to neurons. Complex dynamic behaviors are investigated, including space multi-structure chaotic attractors and coexisting behaviors with space initial offset. Phase portraits, bifurcation diagrams, and Lyapunov exponents are employed to reveal and examine the specific dynamics. Furthermore, microcontroller-based digital hardware platforms are utilized to validate the numerical simulations, and the practicality of the proposed M-HNNs is demonstrated through the design of three corresponding pseudo-random number generators (PRNGs).

Suggested Citation

  • Yuan, Fang & Qi, Yaning & Yu, Xiangcheng & Deng, Yue, 2024. "Design and analysis of grid attractors in memristive Hopfield neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    • Handle: RePEc:eee:chsofr:v:188:y:2024:i:c:s0960077924010300
    DOI: 10.1016/j.chaos.2024.115478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077924010300
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2024.115478?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Wu, Huagan & Bian, Yixuan & Zhang, Yunzhen & Guo, Yixuan & Xu, Quan & Chen, Mo, 2023. "Multi-stable states and synchronicity of a cellular neural network with memristive activation function," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    2. Lai, Qiang & Lai, Cong & Zhang, Hui & Li, Chunbiao, 2022. "Hidden coexisting hyperchaos of new memristive neuron model and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Cao, Hongli & Wang, Yu & Banerjee, Santo & Cao, Yinghong & Mou, Jun, 2024. "A discrete Chialvo–Rulkov neuron network coupled with a novel memristor model: Design, Dynamical analysis, DSP implementation and its application," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    4. Zhang, Sen & Li, Yongxin & Lu, Daorong & Li, Chunbiao, 2024. "A novel memristive synapse-coupled ring neural network with countless attractors and its application," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    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. Ma, Tao & Mou, Jun & Chen, Wanzhong, 2025. "Dynamics and implementation of a functional neuron model with hyperchaotic behavior under electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 190(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. Wang, Chunhua & Luo, Dingwei & Deng, Quanli & Yang, Gang, 2024. "Dynamics analysis and FPGA implementation of discrete memristive cellular neural network with heterogeneous activation functions," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    2. Shi, Qianqian & Qu, Shaocheng & An, Xinlei & Wei, Ziming & Zhang, Chen, 2024. "Three-dimensional m-HR neuron model and its application in medical image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 189(P1).
    3. Ma, Tao & Mou, Jun & Chen, Wanzhong, 2025. "Dynamics and implementation of a functional neuron model with hyperchaotic behavior under electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 190(C).
    4. Shao, Yan & Wu, Fuqiang & Wang, Qingyun, 2025. "Excitability and synchronization of vanadium dioxide memristor-inspired neurons," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 233(C), pages 99-116.
    5. Yuzhou Xi & Yu Ning & Jie Jin & Fei Yu, 2024. "A Dynamic Hill Cipher with Arnold Scrambling Technique for Medical Images Encryption," Mathematics, MDPI, vol. 12(24), pages 1-22, December.
    6. Huang, Keyu & Li, Chunbiao & Cen, Xiaoliang & Chen, Guanrong, 2024. "Constructing chaotic oscillators with memory components," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).
    7. Hu, Jingting & Bao, Han & Xu, Quan & Chen, Mo & Bao, Bocheng, 2024. "Synchronization generations and transitions in two map-based neurons coupled with locally active memristor," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    8. Bashkirtseva, I. & Ryashko, L., 2024. "Dynamical variability, order-chaos transitions, and bursting Canards in the memristive Rulkov neuron model," Chaos, Solitons & Fractals, Elsevier, vol. 186(C).
    9. Wu, Huagan & Gu, Jinxiang & Guo, Yixuan & Chen, Mo & Xu, Quan, 2024. "Biphasic action potentials in an individual cellular neural network cell," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    10. Mirza, Fuat Kaan & Baykaş, Tunçer & Hekimoğlu, Mustafa & Pekcan, Önder & Tunçay, Gönül Paçacı, 2024. "Decoding compositional complexity: Identifying composers using a model fusion-based approach with nonlinear signal processing and chaotic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    11. Ding, Dawei & Wang, Wei & Yang, Zongli & Hu, Yongbing & Wang, Jin & Wang, Mouyuan & Niu, Yan & Zhu, Haifei, 2023. "An n-dimensional modulo chaotic system with expected Lyapunov exponents and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    12. Wu, Huagan & Gu, Jinxiang & Chen, Mo & Wang, Ning & Xu, Quan, 2024. "Bionic firing activities in a dual mem-elements based CNN cell," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).
    13. Li Zhang & Wuyin Jin & Guolong Chen, 2025. "Amplitude control and offset boosting of motion in the neuron-driven mechanical arm," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 98(4), pages 1-13, April.
    14. Han, Zhitang & Sun, Bo & Banerjee, Santo & Mou, Jun, 2024. "Biological neuron modeling based on bifunctional memristor and its application in secure communication," Chaos, Solitons & Fractals, Elsevier, vol. 184(C).
    15. Yaser Shahbazi & Mohsen Mokhtari Kashavar & Abbas Ghaffari & Mohammad Fotouhi & Siamak Pedrammehr, 2025. "CISMN: A Chaos-Integrated Synaptic-Memory Network with Multi-Compartment Chaotic Dynamics for Robust Nonlinear Regression," Mathematics, MDPI, vol. 13(9), pages 1-37, May.
    16. Yu Liu & Yan Zhou & Biyao Guo, 2023. "Hopf Bifurcation, Periodic Solutions, and Control of a New 4D Hyperchaotic System," Mathematics, MDPI, vol. 11(12), pages 1-14, June.
    17. Yangxin Luo & Yuanyuan Huang & Fei Yu & Diqing Liang & Hairong Lin, 2024. "Adaptive Asymptotic Shape Synchronization of a Chaotic System with Applications for Image Encryption," Mathematics, MDPI, vol. 13(1), pages 1-18, December.
    18. Wang, Zhen & Ahmadi, Atefeh & Tian, Huaigu & Jafari, Sajad & Chen, Guanrong, 2023. "Lower-dimensional simple chaotic systems with spectacular features," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    19. Man, Zhenlong, 2023. "Biometric information security based on double chaotic rotating diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    20. Shi, Wei & Min, Fuhong & Yang, Songtao, 2024. "Bifurcation dynamics and FPGA implementation of coupled Fitzhugh-Nagumo neuronal system," Chaos, Solitons & Fractals, Elsevier, vol. 188(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:188:y:2024:i:c:s0960077924010300. 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.