XNOR-BSNN: In-Memory Computing Model for Deep Binarized Spiking Neural Network

This paper proposes a residual binarized spiking neural network (B-SNN) model suited for in-memory computing (IMC) implementation. While in most of the prior arts, due to the nature of spike represented unipolar format, the B-SNN were implemented using either complex or non-regular logic that is not suited for IMC and/or makes the network inflexible. In this work, we present a B-SNN model that per...