Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses
- DOI
- 10.1063/5.0155447
- Published
- 2023-08-16
- Container
- APL Machine Learning
- Publisher
- AIP Publishing
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1063/5.0155447,
title = {Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses},
author = {Nathan Leroux and Danijela Marković and Dédalo Sanz-Hernández and Juan Trastoy and Paolo Bortolotti and Alejandro Schulman and Luana Benetti and Alex Jenkins and Ricardo Ferreira and Julie Grollier and Frank Alice Mizrahi},
year = {2023},
journal = {APL Machine Learning},
doi = {10.1063/5.0155447},
url = {https://doi.org/10.1063/5.0155447}
}RIS
TY - JOUR TI - Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses AU - Nathan Leroux AU - Danijela Marković AU - Dédalo Sanz-Hernández AU - Juan Trastoy AU - Paolo Bortolotti AU - Alejandro Schulman AU - Luana Benetti AU - Alex Jenkins AU - Ricardo Ferreira AU - Julie Grollier AU - Frank Alice Mizrahi PY - 2023 JO - APL Machine Learning DO - 10.1063/5.0155447 UR - https://doi.org/10.1063/5.0155447 ER -
APA
Leroux, N., Marković, D., Sanz-Hernández, D., Trastoy, J., Bortolotti, P., Schulman, A., Benetti, L., Jenkins, A., Ferreira, R., Grollier, J., & Mizrahi, F. A. (2023). Classification of multi-frequency RF signals by extreme learning, using magnetic tunnel junctions as neurons and synapses. APL Machine Learning. https://doi.org/10.1063/5.0155447
Source records
- crossref · retrieved 2026-11-03T10:28:14.573Z