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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Detalles Bibliográficos
Autores principales: Srinivasan, Gopalakrishnan, Roy, Kaushik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6434391/
https://www.ncbi.nlm.nih.gov/pubmed/30941003
http://dx.doi.org/10.3389/fnins.2019.00189

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6434391/
https://www.ncbi.nlm.nih.gov/pubmed/30941003
http://dx.doi.org/10.3389/fnins.2019.00189

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