On Practical Issues for Stochastic STDP Hardware With 1-bit Synaptic Weights

On Practical Issues for Stochastic STDP Hardware With 1-bit Synaptic Weights

In computational neuroscience, synaptic plasticity learning rules are typically studied using the full 64-bit floating point precision computers provide. However, for dedicated hardware implementations, the precision used not only penalizes directly the required memory resources, but also the comput...

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Bibliographic Details
Main Authors: Amirreza Yousefzadeh, Evangelos Stromatias, Miguel Soto, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-10-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural networks
spike timing dependent plasticity
stochastic learning
feature extraction
neuromorphic systems
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2018.00665/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2018.00665/full

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