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Behavioral modeling of multilevel HfO2-based memristors for neuromorphic circuit simulation

  • An artificial neural network based on resistive switching memristors is implemented and simulated in LTspice. The influence of memristor variability and the reduction of the continuous range of synaptic weights into a discrete set of conductance levels is analyzed. To do so, a behavioral model is proposed for multilevel resistive switching memristors based on Al-doped HfO2 dielectrics, and it is implemented in a spice based circuit simulator. The model provides an accurate description of the conductance in the different conductive states in addition to describe the device-to-device variability

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Author: Antonio Javier Perez-Avila, Gerardo Gonzalez-Cordero, Eduardo Perez, Emilio Perez-Bosch Quesada, Mamathamba Kalishettyhalli Mahadevaiah, Christian WengerORCiD, Juan Bautista Roldan, Francisco Jimenez-Molinos
DOI:https://doi.org/10.1109/DCIS51330.2020.9268652
Title of the source (English):XXXV Conference on Design of Circuits and Integrated Systems (DCIS), Segovia, Spain
Document Type:Conference publication peer-reviewed
Language:English
Year of publication:2020
Contributing Corporation:IEEE
Tag:Multilevel switching; RRAM; behavorial model
Faculty/Chair:Fakultät 1 MINT - Mathematik, Informatik, Physik, Elektro- und Informationstechnik / FG Halbleitermaterialien
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