Cargando…
Impact of Synaptic Device Variations on Classification Accuracy in a Binarized Neural Network
Brain-inspired neuromorphic systems (hardware neural networks) are expected to be an energy-efficient computing architecture for solving cognitive tasks, which critically depend on the development of reliable synaptic weight storage (i.e., synaptic device). Although various nanoelectronic devices ha...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2019
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811618/ https://www.ncbi.nlm.nih.gov/pubmed/31645636 http://dx.doi.org/10.1038/s41598-019-51814-5 |