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
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.