IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v161y2022ics0960077922005999.html
   My bibliography  Save this article

A generic voltage-controlled discrete memristor model and its application in chaotic map

Author

Listed:
  • Zhong, Huiyan
  • Li, Guodong
  • Xu, Xiangliang

Abstract

The discrete memristor has aroused increasing interest due to its application prospects. The theory of discrete memory resistors is gradually being refined. In this paper, the generic voltage-controlled discrete memristor model is derived from another perspective - the circuit perspective. And the Simulink model of the discrete memristor model was constructed to implement the simulation. To explore the adaptability of the model, nine discrete memristors are proposed and shown to meet the definition of the memristor. As an application, this paper proposes three discrete memristor-based maps, builds their Simulink model, and analyzes their dynamic behavior relying on the parameters and initials of the system and memristor through the bifurcation diagram, Lyapunov exponent (LE), and spectral entropy complexity. The numerical simulation results show that the three discrete memristor-based maps are better than the original ones in chaotic properties, such as sequence complexity, chaos range, and LE.

Suggested Citation

  • Zhong, Huiyan & Li, Guodong & Xu, Xiangliang, 2022. "A generic voltage-controlled discrete memristor model and its application in chaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
  • Handle: RePEc:eee:chsofr:v:161:y:2022:i:c:s0960077922005999
    DOI: 10.1016/j.chaos.2022.112389
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077922005999
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2022.112389?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. Xiang-Liang Xu & Guo-Dong Li & Wan-Ying Dai & Xiao-Ming Song, 2021. "Multi-Direction Chain And Grid Chaotic System Based On Julia Fractal," FRACTALS (fractals), World Scientific Publishing Co. Pte. Ltd., vol. 29(08), pages 1-20, December.
    2. Peng Yao & Huaqiang Wu & Bin Gao & Jianshi Tang & Qingtian Zhang & Wenqiang Zhang & J. Joshua Yang & He Qian, 2020. "Fully hardware-implemented memristor convolutional neural network," Nature, Nature, vol. 577(7792), pages 641-646, January.
    3. Dmitri B. Strukov & Gregory S. Snider & Duncan R. Stewart & R. Stanley Williams, 2008. "The missing memristor found," Nature, Nature, vol. 453(7191), pages 80-83, May.
    4. Peng, Yuexi & Sun, Kehui & He, Shaobo, 2020. "A discrete memristor model and its application in Hénon map," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).
    5. Yunzhen Zhang & Yuan Ping & Zhili Zhang & Guangzhe Zhao & Cristiana J. Silva, 2021. "Recent Advances in Dimensionality Reduction Modeling and Multistability Reconstitution of Memristive Circuit," Complexity, Hindawi, vol. 2021, pages 1-18, July.
    6. Deng, Yue & Li, Yuxia, 2021. "Bifurcation and bursting oscillations in 2D non-autonomous discrete memristor-based hyperchaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 150(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. Bao, Han & Rong, Kang & Chen, Mo & Zhang, Xi & Bao, Bocheng, 2023. "Multistability and synchronization of discrete maps via memristive coupling," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Xiang, Jianglian & Ren, Junwu & Tan, Manchun, 2022. "Stability analysis for memristor-based stochastic multi-layer neural networks with coupling disturbance," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    3. Yang, Min & Dong, Chengwei & Pan, Hepeng, 2024. "Generating multi-directional hyperchaotic attractors: A novel multi-scroll system based on Julia fractal," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    4. Fan, Zhenyi & Zhang, Chenkai & Wang, Yiming & Du, Baoxiang, 2023. "Construction, dynamic analysis and DSP implementation of a novel 3D discrete memristive hyperchaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    5. Lu, Yang & Gong, Mengxin & Gan, Zhihua & Chai, Xiuli & Cao, Lvchen & Wang, Binjie, 2023. "Exploiting one-dimensional improved Chebyshev chaotic system and partitioned diffusion based on the divide-and-conquer principle for 3D medical model encryption," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    6. Zhao, Qianhan & Bao, Han & Zhang, Xi & Wu, Huagan & Bao, Bocheng, 2024. "Complexity enhancement and grid basin of attraction in a locally active memristor-based multi-cavity map," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    7. Zhao, Zhigao & Chen, Fei & He, Xianghui & Lan, Pengfei & Chen, Diyi & Yin, Xiuxing & Yang, Jiandong, 2024. "A universal hydraulic-mechanical diagnostic framework based on feature extraction of abnormal on-field measurements: Application in micro pumped storage system," Applied Energy, Elsevier, vol. 357(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. Zhang, Shaohua & Zhang, Hongli & Wang, Cong, 2023. "Memristor initial-boosted extreme multistability in the novel dual-memristor hyperchaotic maps," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Ren, Lujie & Mou, Jun & Banerjee, Santo & Zhang, Yushu, 2023. "A hyperchaotic map with a new discrete memristor model: Design, dynamical analysis, implementation and application," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    3. Bao, H. & Gu, Y. & Xu, Q. & Zhang, X. & Bao, B., 2022. "Parallel bi-memristor hyperchaotic map with extreme multistability," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Fan, Zhenyi & Zhang, Chenkai & Wang, Yiming & Du, Baoxiang, 2023. "Construction, dynamic analysis and DSP implementation of a novel 3D discrete memristive hyperchaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    5. Deng, Yue & Li, Yuxia, 2021. "Bifurcation and bursting oscillations in 2D non-autonomous discrete memristor-based hyperchaotic map," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    6. Zhongfang Zhang & Xiaolong Zhao & Xumeng Zhang & Xiaohu Hou & Xiaolan Ma & Shuangzhu Tang & Ying Zhang & Guangwei Xu & Qi Liu & Shibing Long, 2022. "In-sensor reservoir computing system for latent fingerprint recognition with deep ultraviolet photo-synapses and memristor array," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    7. Yijun Li & Jianshi Tang & Bin Gao & Jian Yao & Anjunyi Fan & Bonan Yan & Yuchao Yang & Yue Xi & Yuankun Li & Jiaming Li & Wen Sun & Yiwei Du & Zhengwu Liu & Qingtian Zhang & Song Qiu & Qingwen Li & He, 2023. "Monolithic three-dimensional integration of RRAM-based hybrid memory architecture for one-shot learning," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. Wu, H. & Zhou, J. & Chen, M. & Xu, Q. & Bao, B., 2022. "DC-offset induced asymmetry in memristive diode-bridge-based Shinriki oscillator," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    9. Shchanikov, Sergey & Zuev, Anton & Bordanov, Ilya & Danilin, Sergey & Lukoyanov, Vitaly & Korolev, Dmitry & Belov, Alexey & Pigareva, Yana & Gladkov, Arseny & Pimashkin, Alexey & Mikhaylov, Alexey & K, 2021. "Designing a bidirectional, adaptive neural interface incorporating machine learning capabilities and memristor-enhanced hardware," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    10. Min, Fuhong & Zhang, Wen & Ji, Ziyi & Zhang, Lei, 2021. "Switching dynamics of a non-autonomous FitzHugh-Nagumo circuit with piecewise-linear flux-controlled memristor," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    11. Yuan, Fang & Xing, Guibin & Deng, Yue, 2023. "Flexible cascade and parallel operations of discrete memristor," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    12. Innocenti, Giacomo & Tesi, Alberto & Di Marco, Mauro & Forti, Mauro, 2024. "First integrals can explain coexistence of attractors, multistability, and loss of ideality in circuits with memristors," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    13. Zhang, Shaohua & Zhang, Hongli & Wang, Cong & Lin, Hairong, 2024. "Bionic modeling and dynamics analysis of heterogeneous brain regions connected by memristive synaptic crosstalk," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    14. Rui Wang & Tuo Shi & Xumeng Zhang & Jinsong Wei & Jian Lu & Jiaxue Zhu & Zuheng Wu & Qi Liu & Ming Liu, 2022. "Implementing in-situ self-organizing maps with memristor crossbar arrays for data mining and optimization," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    15. Bao, Han & Rong, Kang & Chen, Mo & Zhang, Xi & Bao, Bocheng, 2023. "Multistability and synchronization of discrete maps via memristive coupling," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    16. Feng, Liang & Hu, Cheng & Yu, Juan & Jiang, Haijun & Wen, Shiping, 2021. "Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    17. Hu, Yongbing & Li, Qian & Ding, Dawei & Jiang, Li & Yang, Zongli & Zhang, Hongwei & Zhang, Zhixin, 2021. "Multiple coexisting analysis of a fractional-order coupled memristive system and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    18. Zhang, Ge & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir & Alzahrani, Faris, 2018. "Dynamical behavior and application in Josephson Junction coupled by memristor," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 290-299.
    19. Djohan Bonnet & Tifenn Hirtzlin & Atreya Majumdar & Thomas Dalgaty & Eduardo Esmanhotto & Valentina Meli & Niccolo Castellani & Simon Martin & Jean-François Nodin & Guillaume Bourgeois & Jean-Michel P, 2023. "Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    20. Xiangpeng Liang & Yanan Zhong & Jianshi Tang & Zhengwu Liu & Peng Yao & Keyang Sun & Qingtian Zhang & Bin Gao & Hadi Heidari & He Qian & Huaqiang Wu, 2022. "Rotating neurons for all-analog implementation of cyclic reservoir computing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.

    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:161:y:2022:i:c:s0960077922005999. 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.