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arXiv · 2111.15250

2D-Motion Detection using SNNs with Graphene-Insulator-Graphene Memristive Synapses

Shubham Pande·Karthi Srinivasan·Suresh Balanethiram·Bhaswar Chakrabarti·Anjan Chakravorty
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Abstract

The event-driven nature of spiking neural networks makes them biologically plausible and more energy-efficient than artificial neural networks. In this work, we demonstrate motion detection of an object in a two-dimensional visual field. The network architecture presented here is biologically plausible and uses CMOS analog leaky integrate-and-fire neurons and ultra-low power multi-layer RRAM synapses. Detailed transistorlevel SPICE simulations show that the proposed structure can accurately and reliably detect complex motions of an object in a two-dimensional visual field.

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Shubham Pande, Karthi Srinivasan, Suresh Balanethiram, Bhaswar Chakrabarti, Anjan Chakravorty. 2021-11-30. 2D-Motion Detection using SNNs with Graphene-Insulator-Graphene Memristive Synapses. https://arxiv.org/abs/2111.15250

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