In situ Parallel Training of Analog Neural Network Using Electrochemical Random-Access Memory

In-memory computing based on non-volatile resistive memory can significantly improve the energy efficiency of artificial neural networks. However, accurate in situ training has been challenging due to the nonlinear and stochastic switching of the resistive memory elements. One promising analog memor...

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Detalhes bibliográficos
Publicado no:Front Neurosci
Main Authors: Li, Yiyang, Xiao, T. Patrick, Bennett, Christopher H., Isele, Erik, Melianas, Armantas, Tao, Hanbo, Marinella, Matthew J., Salleo, Alberto, Fuller, Elliot J., Talin, A. Alec
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2021
Assuntos:
Neuroscience
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8060477/
https://ncbi.nlm.nih.gov/pubmed/33897351
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2021.636127
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