Fast and Efficient Information Transmission with Burst Spikes in Deep Spiking Neural Networks

TL;DR

This paper introduces a novel method using burst spikes and hybrid coding in deep spiking neural networks to enhance inference speed and energy efficiency, addressing limitations of previous approaches.

Contribution

The paper proposes a new information transmission method with burst spikes and hybrid coding for deep SNNs, improving speed and energy efficiency.

Findings

Improved inference energy efficiency

Reduced latency in deep SNNs

Effective hybrid neural coding scheme

Abstract

The spiking neural networks (SNNs) are considered as one of the most promising artificial neural networks due to their energy efficient computing capability. Recently, conversion of a trained deep neural network to an SNN has improved the accuracy of deep SNNs. However, most of the previous studies have not achieved satisfactory results in terms of inference speed and energy efficiency. In this paper, we propose a fast and energy-efficient information transmission method with burst spikes and hybrid neural coding scheme in deep SNNs. Our experimental results showed the proposed methods can improve inference energy efficiency and shorten the latency.