IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v177y2023ics0960077923011268.html
   My bibliography  Save this article

Memristor neurons and their coupling networks based on Edge of Chaos Kernel

Author

Listed:
  • Zhou, Wei
  • Jin, Peipei
  • Dong, Yujiao
  • Liang, Yan
  • Wang, Guangyi

Abstract

Chua's theory of local activity shows that local activity is the origin of complexity, and the complexity can only occur on or near the stable locally active domain, referred to as Edge of Chaos (EOC). Very recently, for the voltage-controlled locally active memristors, a new physical concept dubbed “Edge of Chaos Kernel” (EOCK), which consists of a series combination between a negative resistance and a negative inductance and exhibits the EOC phenomenon of being stable yet potentially unstable, was defined and applied to the Hodgkin-Huxley neural circuit model. When an EOCK is coupled to a passive environment, its stability is disrupted, resulting in the emergence of action potentials, chaos and various complex phenomena. This paper proposes the dual version of the EOCK called as R-C EOCK, which consists of the parallel combination between a negative resistance and a negative capacitance. We show that the actual NbO memristor manufactured by NaMLab essentially belongs to a current-controlled locally active memristor which contains a R-C EOCK and gives the signature of its EOCK and EOC. We construct a second-order neuron based on the NbO memristor when connected in parallel with a passive capacitor, and further prove that only memristors endowed with an EOCK can generate action potential. On this basis, we construct a minimum cellular neural network with only 7 components based on two NbO memristor neurons and a passive coupling resistor, in which neuromorphic behaviors of static and dynamic pattern formation may emerge if and only if the single neuron has an EOCK and is poised on the EOC. The analysis in this paper explains the dynamic mechanism of Smale's paradox, in which two mathematically dead neurons coupled by a passive environment may become alive, under the same or different input current excitation, which are more in line with the actual biological neural networks.

Suggested Citation

  • Zhou, Wei & Jin, Peipei & Dong, Yujiao & Liang, Yan & Wang, Guangyi, 2023. "Memristor neurons and their coupling networks based on Edge of Chaos Kernel," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
  • Handle: RePEc:eee:chsofr:v:177:y:2023:i:c:s0960077923011268
    DOI: 10.1016/j.chaos.2023.114224
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923011268
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2023.114224?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. Wei Yi & Kenneth K. Tsang & Stephen K. Lam & Xiwei Bai & Jack A. Crowell & Elias A. Flores, 2018. "Biological plausibility and stochasticity in scalable VO2 active memristor neurons," Nature Communications, Nature, vol. 9(1), pages 1-10, December.
    2. Suhas Kumar & R. Stanley Williams & Ziwen Wang, 2020. "Third-order nanocircuit elements for neuromorphic engineering," Nature, Nature, vol. 585(7826), pages 518-523, September.
    3. Xu, Quan & Wang, Yiteng & Chen, Bei & Li, Ze & Wang, Ning, 2023. "Firing pattern in a memristive Hodgkin–Huxley circuit: Numerical simulation and analog circuit validation," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    4. M. Prezioso & F. Merrikh-Bayat & B. D. Hoskins & G. C. Adam & K. K. Likharev & D. B. Strukov, 2015. "Training and operation of an integrated neuromorphic network based on metal-oxide memristors," Nature, Nature, vol. 521(7550), pages 61-64, May.
    Full references (including those not matched with items on IDEAS)

    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. Ushakov, Yury & Akther, Amir & Borisov, Pavel & Pattnaik, Debi & Savel’ev, Sergey & Balanov, Alexander G., 2021. "Deterministic mechanisms of spiking in diffusive memristors," Chaos, Solitons & Fractals, Elsevier, vol. 149(C).
    2. Pietro Belleri & Judith Pons i Tarrés & Iain McCulloch & Paul W. M. Blom & Zsolt M. Kovács-Vajna & Paschalis Gkoupidenis & Fabrizio Torricelli, 2024. "Unravelling the operation of organic artificial neurons for neuromorphic bioelectronics," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    3. Dong, Yujiao & Yang, Shuting & Liang, Yan & Wang, Guangyi, 2022. "Neuromorphic dynamics near the edge of chaos in memristive neurons," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Zhiyuan Li & Zhongshao Li & Wei Tang & Jiaping Yao & Zhipeng Dou & Junjie Gong & Yongfei Li & Beining Zhang & Yunxiao Dong & Jian Xia & Lin Sun & Peng Jiang & Xun Cao & Rui Yang & Xiangshui Miao & Ron, 2024. "Crossmodal sensory neurons based on high-performance flexible memristors for human-machine in-sensor computing system," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    5. Tianyu Wang & Jialin Meng & Xufeng Zhou & Yue Liu & Zhenyu He & Qi Han & Qingxuan Li & Jiajie Yu & Zhenhai Li & Yongkai Liu & Hao Zhu & Qingqing Sun & David Wei Zhang & Peining Chen & Huisheng Peng & , 2022. "Reconfigurable neuromorphic memristor network for ultralow-power smart textile electronics," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    6. Ushakov, Yury & Balanov, Alexander & Savel’ev, Sergey, 2021. "Role of noise in spiking dynamics of diffusive memristor driven by heating-cooling cycles," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    7. Xi Zhou & Liang Zhao & Chu Yan & Weili Zhen & Yinyue Lin & Le Li & Guanlin Du & Linfeng Lu & Shan-Ting Zhang & Zhichao Lu & Dongdong Li, 2023. "Thermally stable threshold selector based on CuAg alloy for energy-efficient memory and neuromorphic computing applications," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. See-On Park & Hakcheon Jeong & Jongyong Park & Jongmin Bae & Shinhyun Choi, 2022. "Experimental demonstration of highly reliable dynamic memristor for artificial neuron and neuromorphic computing," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    9. Ke Yang & Yanghao Wang & Pek Jun Tiw & Chaoming Wang & Xiaolong Zou & Rui Yuan & Chang Liu & Ge Li & Chen Ge & Si Wu & Teng Zhang & Ru Huang & Yuchao Yang, 2024. "High-order sensory processing nanocircuit based on coupled VO2 oscillators," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    10. Xu, Quan & Wang, Yiteng & Wu, Huagan & Chen, Mo & Chen, Bei, 2024. "Periodic and chaotic spiking behaviors in a simplified memristive Hodgkin-Huxley circuit," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    11. Ying, Jiajie & Min, Fuhong & Wang, Guangyi, 2023. "Neuromorphic behaviors of VO2 memristor-based neurons," Chaos, Solitons & Fractals, Elsevier, vol. 175(P2).
    12. Sang Hyun Sung & Tae Jin Kim & Hyera Shin & Tae Hong Im & Keon Jae Lee, 2022. "Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    13. 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.
    14. Ui Yeon Won & Quoc An Vu & Sung Bum Park & Mi Hyang Park & Van Dam Do & Hyun Jun Park & Heejun Yang & Young Hee Lee & Woo Jong Yu, 2023. "Multi-neuron connection using multi-terminal floating–gate memristor for unsupervised learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    15. Fanfan Li & Dingwei Li & Chuanqing Wang & Guolei Liu & Rui Wang & Huihui Ren & Yingjie Tang & Yan Wang & Yitong Chen & Kun Liang & Qi Huang & Mohamad Sawan & Min Qiu & Hong Wang & Bowen Zhu, 2024. "An artificial visual neuron with multiplexed rate and time-to-first-spike coding," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    16. Ruibin Mao & Bo Wen & Arman Kazemi & Yahui Zhao & Ann Franchesca Laguna & Rui Lin & Ngai Wong & Michael Niemier & X. Sharon Hu & Xia Sheng & Catherine E. Graves & John Paul Strachan & Can Li, 2022. "Experimentally validated memristive memory augmented neural network with efficient hashing and similarity search," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    17. 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).
    18. Arnab Pal & Zichun Chai & Junkai Jiang & Wei Cao & Mike Davies & Vivek De & Kaustav Banerjee, 2024. "An ultra energy-efficient hardware platform for neuromorphic computing enabled by 2D-TMD tunnel-FETs," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    19. Parshina, Liubov & Novodvorsky, Oleg & Khramova, Olga & Gusev, Dmitriy & Polyakov, Alexander & Mikhalevsky, Vladimir & Cherebilo, Elena, 2021. "Laser synthesis of non-volatile memristor structures based on tantalum oxide thin films," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    20. Bin Gao & Ying Zhou & Qingtian Zhang & Shuanglin Zhang & Peng Yao & Yue Xi & Qi Liu & Meiran Zhao & Wenqiang Zhang & Zhengwu Liu & Xinyi Li & Jianshi Tang & He Qian & Huaqiang Wu, 2022. "Memristor-based analogue computing for brain-inspired sound localization with in situ training," Nature Communications, Nature, vol. 13(1), pages 1-8, 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:177:y:2023:i:c:s0960077923011268. 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.