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

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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Bibliographic Details
Main Authors: Fernando Leonel Aguirre, Eszter Piros, Nico Kaiser, Tobias Vogel, Stephan Petzold, Jonas Gehrunger, Timo Oster, Christian Hochberger, Jordi Suñé, Lambert Alff, Enrique Miranda
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Micromachines
Subjects:
RRAM
neural networks
curve fitting
dynamic memdiode
memristor
Online Access:https://www.mdpi.com/2072-666X/13/11/2002

Internet

https://www.mdpi.com/2072-666X/13/11/2002

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