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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...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596564/ https://www.ncbi.nlm.nih.gov/pubmed/33122647 http://dx.doi.org/10.1038/s41467-020-19203-z |