Data-driven RRAM device models using Kriging interpolation.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
08 Apr 2022
08 Apr 2022
Historique:
received:
21
12
2021
accepted:
16
03
2022
entrez:
9
4
2022
pubmed:
10
4
2022
medline:
10
4
2022
Statut:
epublish
Résumé
A two-tier Kriging interpolation approach is proposed to model jump tables for resistive switches. Originally developed for mining and geostatistics, its locality of the calculation makes this approach particularly powerful for modeling electronic devices with complex behavior landscape and switching noise, like RRAM. In this paper, a first Kriging model is used to model and predict the mean in the signal, followed up by a second Kriging step used to model the standard deviation of the switching noise. We use 36 synthetic datasets covering a broad range of different mean and standard deviation Gaussian distributions to test the validity of our approach. We also show the applicability to experimental data obtained from TiO
Identifiants
pubmed: 35396453
doi: 10.1038/s41598-022-09556-4
pii: 10.1038/s41598-022-09556-4
pmc: PMC8993845
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
5963Subventions
Organisme : George Washington University
ID : Cross-Disciplinary Research Fund
Organisme : George Washington University
ID : University Facilitating Fund
Organisme : Office of Naval Research
ID : N00014-20-1-2031
Informations de copyright
© 2022. The Author(s).
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