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Role of noise in spiking dynamics of diffusive memristor driven by heating-cooling cycles

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posted on 2021-02-22, 11:44 authored by Yury Ushakov, Alexander BalanovAlexander Balanov, Sergey SavelievSergey Saveliev
Recently fabricated and measured diffusive memristors have attracted a significant interest as one of the best candidates to mimic neuron activities and to implement novel computing paradigms. Such devices are capable of exhibiting a combination of dynamical, chaotic, and stochastic phenomena needed for efficient neuromorphic computational systems. However, understanding of contribution and interplay of deterministic and stochastic dynamics to the functional properties of a diffusive memristor is still an open problem. Here, we propose a perturbative approach allowing to separate an influence of noise from regular motion of nanoparticles in diffusive memristors. We demonstrate that noise, coupled with a deterministic degree of freedom in artificial neurons based on diffusive memristors, originates a novel spiking mechanism absent in noiseless systems. The developed formalism suggests an approach towards deterministic modeling of stochastic artificial neurons.

Funding

Neuromorphic memristive circuits to simulate inhibitory and excitatory dynamics of neuron networks: from physiological similarities to deep learning

Engineering and Physical Sciences Research Council

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History

School

  • Science

Department

  • Physics

Published in

Chaos, Solitons and Fractals

Volume

145

Publisher

Elsevier

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Chaos, Solitons and Fractals and the definitive published version is available at https://doi.org/10.1016/j.chaos.2021.110803.

Acceptance date

2021-02-18

Publication date

2021-03-08

Copyright date

2021

ISSN

0960-0779

Language

  • en

Depositor

Dr Yury Ushakov. Deposit date: 19 February 2021

Article number

110803

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