Surrogate gradients for analog neuromorphic computing

To rapidly process temporal information at a low metabolic cost, biological neurons integrate inputs as an analog sum, but communicate with spikes, binary events in time. Analog neuromorphic hardware uses the same principles to emulate spiking neural networks with exceptional energy efficiency. Howe...

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Detalles Bibliográficos
Autores principales: Cramer, Benjamin, Billaudelle, Sebastian, Kanya, Simeon, Leibfried, Aron, Grübl, Andreas, Karasenko, Vitali, Pehle, Christian, Schreiber, Korbinian, Stradmann, Yannik, Weis, Johannes, Schemmel, Johannes, Zenke, Friedemann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Physical Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794842/
https://www.ncbi.nlm.nih.gov/pubmed/35042792
http://dx.doi.org/10.1073/pnas.2109194119

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8794842/
https://www.ncbi.nlm.nih.gov/pubmed/35042792
http://dx.doi.org/10.1073/pnas.2109194119

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