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

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