Unsupervised Learning on Resistive Memory Array Based Spiking Neural Networks

Unsupervised Learning on Resistive Memory Array Based Spiking Neural Networks

Spiking Neural Networks (SNNs) offer great potential to promote both the performance and efficiency of real-world computing systems, considering the biological plausibility of SNNs. The emerging analog Resistive Random Access Memory (RRAM) devices have drawn increasing interest as potential neuromor...

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Bibliographic Details
Main Authors: Yilong Guo, Huaqiang Wu, Bin Gao, He Qian
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-08-01
Series:Frontiers in Neuroscience
Subjects:
unsupervised learning
spiking neural network (SNN)
memristor
RRAM (resistive random access memories)
1T1R RRAM
STDP
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2019.00812/full

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https://www.frontiersin.org/article/10.3389/fnins.2019.00812/full

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