SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron

SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks With at Most One Spike per Neuron

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient. Unlike the non-spiking counterparts, most of the existing SNN simulation frameworks are not practically...

Full description

Bibliographic Details
Main Authors: Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini, Timothée Masquelier
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-07-01
Series:Frontiers in Neuroscience
Subjects:
convolutional spiking neural networks
time-to-first-spike coding
one spike per neuron
STDP
reward-modulated STDP
tensor-based computing
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00625/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2019.00625/full

Similar Items