Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses

In an increasingly data-rich world the need for developing computing systems that cannot only process, but ideally also interpret big data is becoming continuously more pressing. Brain-inspired concepts have shown great promise towards addressing this need. Here we demonstrate unsupervised learning...

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Detalles Bibliográficos
Autores principales: Serb, Alexander, Bill, Johannes, Khiat, Ali, Berdan, Radu, Legenstein, Robert, Prodromakis, Themis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5056401/
https://www.ncbi.nlm.nih.gov/pubmed/27681181
http://dx.doi.org/10.1038/ncomms12611

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5056401/
https://www.ncbi.nlm.nih.gov/pubmed/27681181
http://dx.doi.org/10.1038/ncomms12611

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