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Graphene memristive synapses for high precision neuromorphic computing

Memristive crossbar architectures are evolving as powerful in-memory computing engines for artificial neural networks. However, the limited number of non-volatile conductance states offered by state-of-the-art memristors is a concern for their hardware implementation since trained weights must be ro...

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Detalhes bibliográficos
Publicado no:Nat Commun
Main Authors: Schranghamer, Thomas F., Oberoi, Aaryan, Das, Saptarshi
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7596564/
https://ncbi.nlm.nih.gov/pubmed/33122647
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41467-020-19203-z
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