Graph-Based Spatio-Temporal Backpropagation for Training Spiking Neural Networks

Yulong Yan,Haoming Chu,Xin Chen,Yi Jin,Yuxiang Huan,Lirong Zheng,Zhuo Zou

2021 IEEE 3rd International Conference on Artificial Intelligence Circuits and Systems (AICAS)（2021）

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摘要

Dedicated hardware for spiking neural networks (SNN) reduces energy consumption with spike-driven computing. This paper proposes a graph-based spatio-temporal backpropagation (G-STBP) to train SNN, aiming to enhance spike sparsity for energy efficiency, while ensuring the accuracy. A differentiable leaky integrate-and-fire (LIF) model is suggested to establish the backpropagation path. The sparse ...

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关键词

spiking neural network (SNN),spike sparsity,graph-based spatio-temporal backpropagation (G-STBP),leaky integrate-and-fire (LIF),recurrent network

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