SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training

SSTDP: Supervised Spike Timing Dependent Plasticity for Efficient Spiking Neural Network Training

Spiking Neural Networks (SNNs) are a pathway that could potentially empower low-power event-driven neuromorphic hardware due to their spatio-temporal information processing capability and high biological plausibility. Although SNNs are currently more efficient than artificial neural networks (ANNs),...

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Autores principales: Fangxin Liu, Wenbo Zhao, Yongbiao Chen, Zongwu Wang, Tao Yang, Li Jiang
Formato: article
Lenguaje:EN
Publicado: Frontiers Media S.A. 2021
Materias:
spiking neural network
gradient descent backpropagation
neuromorphic computing
spike-time-dependent plasticity
deep learning
efficient training
Neurosciences. Biological psychiatry. Neuropsychiatry
RC321-571
Acceso en línea:https://doaj.org/article/f6a5d3a0ea4e4e48a939a0bc137d6667
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https://doaj.org/article/f6a5d3a0ea4e4e48a939a0bc137d6667

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