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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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| Pubblicato in: | Nat Commun |
|---|---|
| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2020
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| Soggetti: | |
| Accesso online: | 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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