Backpropagation With Sparsity Regularization for Spiking Neural Network Learning

Backpropagation With Sparsity Regularization for Spiking Neural Network Learning

The spiking neural network (SNN) is a possible pathway for low-power and energy-efficient processing and computing exploiting spiking-driven and sparsity features of biological systems. This article proposes a sparsity-driven SNN learning algorithm, namely backpropagation with sparsity regularizatio...

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Bibliographic Details
Main Authors: Yulong Yan, Haoming Chu, Yi Jin, Yuxiang Huan, Zhuo Zou, Lirong Zheng
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-04-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural network
backpropagation
sparsity regularization
spiking sparsity
synaptic sparsity
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2022.760298/full

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https://www.frontiersin.org/articles/10.3389/fnins.2022.760298/full

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