Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks

Understand

The Spiking Neural Network (SNN), as one of the biologically inspired neural network infrastructures, has drawn increasing attention recently.

• It adopts binary spike activations to transmit information, thus the multiplications of activations and weights can be substituted by additions, which brings high energy efficiency.
• However, in the paper, we theoretically and experimentally prove that the binary spike activation map cannot carry enough information, thus causing information loss and resulting in accuracy decreasing.
• To handle the problem, we propose a ternary spike neuron to transmit information.