Trainable hardware for dynamical computing using error backpropagation through physical media

Neural networks are currently implemented on digital Von Neumann machines, which do not fully leverage their intrinsic parallelism. We demonstrate how to use a novel class of reconfigurable dynamical systems for analogue information processing, mitigating this problem. Our generic hardware platform...

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Detalles Bibliográficos
Autores principales: Hermans, Michiel, Burm, Michaël, Van Vaerenbergh, Thomas, Dambre, Joni, Bienstman, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Pub. Group 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382991/
https://www.ncbi.nlm.nih.gov/pubmed/25801303
http://dx.doi.org/10.1038/ncomms7729

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382991/
https://www.ncbi.nlm.nih.gov/pubmed/25801303
http://dx.doi.org/10.1038/ncomms7729

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