Direct Training via Backpropagation for Ultra-low Latency Spiking Neural Networks with Multi-threshold

Understand

Spiking neural networks (SNNs) can utilize spatio-temporal information and have a nature of energy efficiency which is a good alternative to deep neural networks(DNNs).

• The event-driven information processing makes SNNs can reduce the expensive computation of DNNs and save a lot of energy consumption.
• However, high training and inference latency is a limitation of the development of deeper SNNs.
• SNNs usually need tens or even hundreds of time steps during the training and inference process which causes not only the increase of latency but also the waste of energy consumption.