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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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Autori principali: Fernando Leonel Aguirre, Eszter Piros, Nico Kaiser, Tobias Vogel, Stephan Petzold, Jonas Gehrunger, Timo Oster, Christian Hochberger, Jordi Suñé, Lambert Alff, Enrique Miranda
Natura: Artigo
Lingua:Inglês
Pubblicazione: MDPI AG 2022-11-01
Serie:Micromachines
Soggetti:
RRAM
neural networks
curve fitting
dynamic memdiode
memristor
Accesso online:https://www.mdpi.com/2072-666X/13/11/2002
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