Direction Finding by Reconfigurable Metasurface Via Machine Learning
This study deals with the use of machine learning to assist a reconfigurable metasurface in direction finding. A comparative analysis between different models is made to evaluate their effectiveness based on the assessment of the performances through different metrics such as the root mean square error (RMSE), mean absolute angular error (MAAE) and determination coefficient.
Authors
- Nawel Meftah
- Shah Nawaz Burokur (ORCID: https://orcid.org/0000-0002-1848-4862)
- Mohammed Nabil El Korso (ORCID: https://orcid.org/0000-0002-5489-4308)
- Badreddine Ratni (ORCID: https://orcid.org/0000-0001-8610-4713)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Paris Nanterre (FR)
- Laboratoire des signaux et systèmes (FR)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1109/ap-s/cnc-usnc-ursi55537.2025.11266588
- Primary Topic
- Metamaterials and Metasurfaces Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00