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Graphene memristive synapses for high precision neuromorphic computing
- Source :
- Nature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
- Publication Year :
- 2020
- Publisher :
- Nature Portfolio, 2020.
-
Abstract
- Designing efficient and low power memristors-based neuromorphic systems remains a challenge. Here, the authors present graphene-based multi-level (>16) and non-volatile memristive synapses with arbitrarily programmable conductance states capable of weight assignment based on k-means clustering.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.130631a23e64efc851890dbc7347d88
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-020-19203-z