Efficient training of spiking neural networks with temporally-truncated local backpropagation through time

Directly training spiking neural networks (SNNs) has remained challenging due to complex neural dynamics and intrinsic non-differentiability in firing functions. The well-known backpropagation through time (BPTT) algorithm proposed to train SNNs suffers from large memory footprint and prohibits back...

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Detalles Bibliográficos
Autores principales: Guo, Wenzhe, Fouda, Mohammed E., Eltawil, Ahmed M., Salama, Khaled Nabil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117667/
https://www.ncbi.nlm.nih.gov/pubmed/37090791
http://dx.doi.org/10.3389/fnins.2023.1047008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117667/
https://www.ncbi.nlm.nih.gov/pubmed/37090791
http://dx.doi.org/10.3389/fnins.2023.1047008

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