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Amir Akther

Publications and source records attributed to Amir Akther.

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Stress-induced Artificial neuron spiking in Diffusive memristors

Diffusive memristors owing to their ability to produce current spiking when a constant or slowly changing voltage is applied are competitive candidates for the development of artificial electronic neurons. These artificial neurons can be integrated into various prospective autonomous and robotic systems as sensors, e.g. ones implementing object grasping and classification. We report here Ag nanoparticle-based diffusive memristor prepared on a flexible polyethylene terephthalate (PET) substrate in which the electric spiking behaviour was induced by the electric voltage under an additional stimulus of external mechanical impact. By changing the magnitude and frequency of the mechanical impact, we are able to manipulate the spiking response of our artificial neuron. This functionality to control the spiking characterstics paves a pathway for the development of touch-perception sensors that can convert local pressure into electrical spikes for further processing in neural networks. We have proposed a mathematical model which captures the operation principle of the fabricated memristive sensors and qualitatively describes the measured spiking behaviour.

physics.app-ph

Stochastic Instabilities of the Diffusive Memristor

Recently created diffusive memristors have garnered significant research interest owing to their distinctive capability to generate a diverse array of spike dynamics which are similar in nature to those found in biological cells. This gives the memristor an opportunity to be used in a wide range of applications, specifically within neuromorphic systems. The diffusive memristor is known to produce regular, chaotic and stochastic behaviors which leads to interesting phenomena resulting from the interactions between the behavioral properties. The interactions along with the instabilities that lead to the unique spiking phenomena are not fully understood due to the complexities associated with examining the stochastic properties within the diffusive memristor. In this work, we analyze both the classical and the noise induced bifurcations that a set of stochastic differential equations, justified through a Fokker-Planck equation used to model the diffusive memristor, can produce. Finally, we replicate the results of the numerical stochastic threshold phenomena with experimentally measured spiking.

physics.app-ph