A Soft-Pruning Method Applied During Training of Spiking Neural Networks for In-memory Computing Applications

A Soft-Pruning Method Applied During Training of Spiking Neural Networks for In-memory Computing Applications

Inspired from the computational efficiency of the biological brain, spiking neural networks (SNNs) emulate biological neural networks, neural codes, dynamics, and circuitry. SNNs show great potential for the implementation of unsupervised learning using in-memory computing. Here, we report an algori...

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Bibliographic Details
Main Authors: Yuhan Shi, Leon Nguyen, Sangheon Oh, Xin Liu, Duygu Kuzum
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-04-01
Series:Frontiers in Neuroscience
Subjects:
spiking neural networks
unsupervised learning
handwriting recognition
pruning
in-memory computing
emerging non-volatile memory
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00405/full

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