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. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

Diffusive memristors, considered as one of the best candidates to mimic neuron activities and implement novel computing paradigms, exhibit a combination of dynamical, chaotic, and stochastic phenomena, but understanding the contribution of deterministic and stochastic dynamics to their functional properties remains an open problem.