Optimizing BCPNN Learning Rule for Memory Access

Simulation of large scale biologically plausible spiking neural networks, e.g., Bayesian Confidence Propagation Neural Network (BCPNN), usually requires high-performance supercomputers with dedicated accelerators, such as GPUs, FPGAs, or even Application-Specific Integrated Circuits (ASICs). Almost...

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Detalles Bibliográficos
Autores principales: Yang, Yu, Stathis, Dimitrios, Jordão, Rodolfo, Hemani, Ahmed, Lansner, Anders
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487417/
https://www.ncbi.nlm.nih.gov/pubmed/32982673
http://dx.doi.org/10.3389/fnins.2020.00878

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7487417/
https://www.ncbi.nlm.nih.gov/pubmed/32982673
http://dx.doi.org/10.3389/fnins.2020.00878

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