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...

Descripción completa

Detalles Bibliográficos
Autores principales: Yan, Yulong, Chu, Haoming, Jin, Yi, Huan, Yuxiang, Zou, Zhuo, Zheng, Lirong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047717/
https://www.ncbi.nlm.nih.gov/pubmed/35495028
http://dx.doi.org/10.3389/fnins.2022.760298

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9047717/
https://www.ncbi.nlm.nih.gov/pubmed/35495028
http://dx.doi.org/10.3389/fnins.2022.760298

Ejemplares similares