ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing

ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing

In this work, we propose ReStoCNet, a residual stochastic multilayer convolutional Spiking Neural Network (SNN) composed of binary kernels, to reduce the synaptic memory footprint and enhance the computational efficiency of SNNs for complex pattern recognition tasks. ReStoCNet consists of an input l...

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Bibliographic Details
Main Authors: Gopalakrishnan Srinivasan, Kaushik Roy
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-03-01
Series:Frontiers in Neuroscience
Subjects:
convolutional SNN
spiking ResNet
binary kernels
probabilistic STDP
unsupervised feature learning
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00189/full

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