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

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...

Full description

Bibliographic Details
Main Authors: Wenzhe Guo, Mohammed E. Fouda, Ahmed M. Eltawil, Khaled Nabil Salama
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-04-01
Series:Frontiers in Neuroscience
Subjects:
backpropagation through time
deep learning
energy-efficient training
local learning
neuromorphic computing
spiking neural networks
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2023.1047008/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2023.1047008/full

Similar Items