Convolutional networks for fast, energy-efficient neuromorphic computing

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communic...

詳細記述

保存先:
書誌詳細
出版年:Proc Natl Acad Sci U S A
主要な著者: Esser, Steven K., Merolla, Paul A., Arthur, John V., Cassidy, Andrew S., Appuswamy, Rathinakumar, Andreopoulos, Alexander, Berg, David J., McKinstry, Jeffrey L., Melano, Timothy, Barch, Davis R., di Nolfo, Carmelo, Datta, Pallab, Amir, Arnon, Taba, Brian, Flickner, Myron D., Modha, Dharmendra S.
フォーマット: Artigo
言語:Inglês
出版事項: National Academy of Sciences 2016
主題:
Physical Sciences
オンライン･アクセス:https://ncbi.nlm.nih.gov/pmc/articles/PMC5068316/
https://ncbi.nlm.nih.gov/pubmed/27651489
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1604850113
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