Boolean learning under noise-perturbations in hardware neural networks
A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems have recently implemented some or all of these operations, yet the focus was placed on addressing technological challenges...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2020-06-01
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| Series: | Nanophotonics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/nanoph-2020-0171 |