Hardware Implementations of a Deep Learning Approach to Optimal Configuration of Reconfigurable Intelligence Surfaces.

Martín-Martín A, Padial-Allué R, Castillo E, Parrilla L, Parellada-Serrano I, Morán A, García A

DOI: 10.3390/s24030899
Published: 2024 Jan 30
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.3390/s24030899,
  title = {Hardware Implementations of a Deep Learning Approach to Optimal Configuration of Reconfigurable Intelligence Surfaces.},
  author = {Martín-Martín A and Padial-Allué R and Castillo E and Parrilla L and Parellada-Serrano I and Morán A and García A},
  year = {2024},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s24030899},
  url = {https://doi.org/10.3390/s24030899}
}

RIS

TY  - JOUR
TI  - Hardware Implementations of a Deep Learning Approach to Optimal Configuration of Reconfigurable Intelligence Surfaces.
AU  - Martín-Martín A
AU  - Padial-Allué R
AU  - Castillo E
AU  - Parrilla L
AU  - Parellada-Serrano I
AU  - Morán A
AU  - García A
PY  - 2024
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s24030899
UR  - https://doi.org/10.3390/s24030899
ER  -

APA

A, M., R, P., E, C., L, P., I, P., A, M., & A, G. (2024). Hardware Implementations of a Deep Learning Approach to Optimal Configuration of Reconfigurable Intelligence Surfaces.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s24030899

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pubmed · retrieved 2026-11-10T07:05:11.691Z