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Deterministic mechanisms of spiking in diffusive memristors

Diffusive memristors, which have been recently fabricated and measured, attract a significant interest being among 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 the contribution of deterministic and stochastic dynamics to the functional properties of a diffusive memristor is still an open problem. To study the deterministic mechanisms governing the dynamics of diffusive memristors, we analyze a model of a memristive circuit when the effects of the temperature noise are neglected. We reveal instabilities, which shape the current-voltage characteristic of the device and imply the onset of current self-oscillations. Finally, the results of modeling are compared with experimentally measured current-voltage characteristics.

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

149

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.2021.110997.

Acceptance date

19/04/2021

Publication date

2021-06-06

Copyright date

2021

ISSN

0960-0779

Language

en

Depositor

Dr Yury Ushakov. Deposit date: 12 May 2021

Article number

110997

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