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.
Guardado en:
Autores principales: | Yuhan Shi, Leon Nguyen, Sangheon Oh, Xin Liu, Foroozan Koushan, John R. Jameson, Duygu Kuzum |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2018
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Materias: | |
Acceso en línea: | https://doaj.org/article/710e25b6bca046438cd3b187dd5be197 |
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