Unsupervised Learning on Resistive Memory Array Based Spiking Neural Networks

Spiking Neural Networks (SNNs) offer great potential to promote both the performance and efficiency of real-world computing systems, considering the biological plausibility of SNNs. The emerging analog Resistive Random Access Memory (RRAM) devices have drawn increasing interest as potential neuromor...

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Detalles Bibliográficos
Autores principales: Guo, Yilong, Wu, Huaqiang, Gao, Bin, Qian, He
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691091/
https://www.ncbi.nlm.nih.gov/pubmed/31447634
http://dx.doi.org/10.3389/fnins.2019.00812

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6691091/
https://www.ncbi.nlm.nih.gov/pubmed/31447634
http://dx.doi.org/10.3389/fnins.2019.00812

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