Neuroinspired unsupervised learning and pruning with subquantum CBRAM arrays
To realize the potential of resistive RAM crossbar arrays as platforms for neuromorphic computing, reduced network-level energy consumption must be achieved. Here, the authors use a hardware/software co-design approach to realize reduced energy consumption during network training for the network.
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| Auteurs principaux: | , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2018
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/710e25b6bca046438cd3b187dd5be197 |
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