Implementation of Dropout Neuronal Units Based on Stochastic Memristive Devices in Neural Networks with High Classification Accuracy

Neural networks based on memristive devices have achieved great progress recently. However, memristive synapses with nonlinearity and asymmetry seriously limit the classification accuracy. Moreover, insufficient number of training samples in many cases also have negative effect on the classification...

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Detalles Bibliográficos
Autores principales: Huang, He‐Ming, Xiao, Yu, Yang, Rui, Yu, Ye‐Tian, He, Hui‐Kai, Wang, Zhe, Guo, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Communications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509653/
https://www.ncbi.nlm.nih.gov/pubmed/32999852
http://dx.doi.org/10.1002/advs.202001842

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509653/
https://www.ncbi.nlm.nih.gov/pubmed/32999852
http://dx.doi.org/10.1002/advs.202001842

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