Fast Fitting of the Dynamic Memdiode Model to the Conduction Characteristics of RRAM Devices Using Convolutional Neural Networks

In this paper, the use of Artificial Neural Networks (ANNs) in the form of Convolutional Neural Networks (AlexNET) for the fast and energy-efficient fitting of the Dynamic Memdiode Model (DMM) to the conduction characteristics of bipolar-type resistive switching (RS) devices is investigated. Despite...

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Detalles Bibliográficos
Autores principales: Aguirre, Fernando Leonel, Piros, Eszter, Kaiser, Nico, Vogel, Tobias, Petzold, Stephan, Gehrunger, Jonas, Oster, Timo, Hochberger, Christian, Suñé, Jordi, Alff, Lambert, Miranda, Enrique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698277/
https://www.ncbi.nlm.nih.gov/pubmed/36422434
http://dx.doi.org/10.3390/mi13112002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9698277/
https://www.ncbi.nlm.nih.gov/pubmed/36422434
http://dx.doi.org/10.3390/mi13112002

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