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Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the traini...

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Detalles Bibliográficos
Autores principales: Mostafa, Hesham, Pedroni, Bruno, Sheik, Sadique, Cauwenberghs, Gert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5592276/
https://www.ncbi.nlm.nih.gov/pubmed/28932180
http://dx.doi.org/10.3389/fnins.2017.00496