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Intermittent and metastable chaos in a memristive artificial neuron with inertia

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  • Wojtusiak, A.M.
  • Balanov, A.G.
  • Savel’ev, S.E.

Abstract

Inspired by rapid experimental development of diffusive memristors, we propose a computational model of a memristive artificial neuron that takes into consideration inertia of metallic nanoparticles within the dielectric layer of the core-memristor. This model displays rich nonlinear dynamics, which has been speculated to be key for successful emulation of living biological neurons by neuromorphic devices. We found out four characteristic dynamical regimes realized in the system depending on inertness of the nanoparticles. For low-inertia particles, the artificial neuron biased by an applied DC-voltage demonstrates either steady state or regular periodic oscillations. For higher inertia, metastable and intermittent chaos can appear in the system. We analyse the transitions between these regimes and draw parallels between our model and biological neurons.

Suggested Citation

  • Wojtusiak, A.M. & Balanov, A.G. & Savel’ev, S.E., 2021. "Intermittent and metastable chaos in a memristive artificial neuron with inertia," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:chsofr:v:142:y:2021:i:c:s0960077920307773
    DOI: 10.1016/j.chaos.2020.110383
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    References listed on IDEAS

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    1. Suhas Kumar & John Paul Strachan & R. Stanley Williams, 2017. "Chaotic dynamics in nanoscale NbO2 Mott memristors for analogue computing," Nature, Nature, vol. 548(7667), pages 318-321, August.
    2. Sergey E. Savel’ev & Fabio Marchesoni & Alexander M. Bratkovsky, 2013. "Mesoscopic resistive switch: non-volatility, hysteresis and negative differential resistance," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 86(12), pages 1-6, December.
    3. Ming Wang & Chong Bi & Ling Li & Shibing Long & Qi Liu & Hangbing Lv & Nianduan Lu & Pengxiao Sun & Ming Liu, 2014. "Thermoelectric Seebeck effect in oxide-based resistive switching memory," Nature Communications, Nature, vol. 5(1), pages 1-6, December.
    4. 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.
    5. Stuart B. Field & M. Klaus & M. G. Moore & Franco Nori, 1997. "Chaotic dynamics of falling disks," Nature, Nature, vol. 388(6639), pages 252-254, July.
    6. James A. Roberts & Leonardo L. Gollo & Romesh G. Abeysuriya & Gloria Roberts & Philip B. Mitchell & Mark W. Woolrich & Michael Breakspear, 2019. "Metastable brain waves," Nature Communications, Nature, vol. 10(1), pages 1-17, December.
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