Gaussian synapses for probabilistic neural networks
Designing large-scale hardware implementation of Probabilistic Neural Network for energy efficient neuromorphic computing systems remains a challenge. Here, the authors propose an hardware design based on MoS2/BP heterostructures as reconfigurable Gaussian synapses enabling EEG patterns recognition.
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Autores principales: | Amritanand Sebastian, Andrew Pannone, Shiva Subbulakshmi Radhakrishnan, Saptarshi Das |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/ad20e8a07db343ebacc0a4a6dcfc367e |
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