Power and Area-Efficient XNOR-AND Hybrid Binary Neural Networks Using TFT-Type Synaptic Device

A novel XNOR- AND hybrid binary neural network (BNN) using a TFT-type synaptic device is proposed to reduce the area and power consumption of the synaptic array. Replacing some parts of the network from the XNOR operation to the AND operation results in expressing weight and input with a single cell and single word line. In the case of replacing the operation of the fully-connected (FC) layer with the AND operation, the accuracy of VGG9 BNN for CIFAR-10 datasets drops by about 1%, while the number of cells in the synaptic array decreases by 33.7%. Using the previously proposed TFT-type synaptic devices, the proposed method reduces power consumption by ~25%.