Role of noise in spiking dynamics of diffusive memristor driven by heating-cooling cycles. (April 2021)

• Record Type: Journal Article
• Authors: Ushakov, Yury; Balanov, Alexander; Savel'ev, Sergey
• Is Part Of: Chaos, solitons and fractals. Volume 145(2021)
• Publication Date: 2021-04
• Subjects: Diffusive memristor -- Stochastic dynamics -- Spiking; 00-01 -- 99-00; Chaotic behavior in systems -- Periodicals; Solitons -- Periodicals; Fractals -- Periodicals; Chaotic behavior in systems; Fractals; Solitons; Periodicals; 003.7
• DOI: 10.1016/j.chaos.2021.110803
• Languages: English
• ISSNs: 0960-0779

Abstract

Highlights: An efficient one-particle approximation model for memristor-based artificial neuron. Deterministic modeling of a stochastic artificial neuron. Perturbative approach to revealing noise-induced dynamical effects. Heating-cooling cycles in a diffusive memristor, originating irregular spiking. Abstract: 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.