Advanced learning-based approaches for reflectarrays design

Abstract : The problem of efficiently and effectively compute the response (i.e., reflection coefficients) of next-generation reflectarray elements with wide number of degrees-of-freedom is addressed in this work. Towards this end, a machine learning-based approach based on advanced Kriging strategies is exploited (instead of classical full-wave solvers) in order to predict the response of complex unit cells of interest for the design of high-performance reflectarrays. Preliminary numerical results aimed at comparing the accuracy and efficiency of the proposed methodology with respect to standard full-wave approaches are illustrated.
Type de document :
Communication dans un congrès
11th European Conference on Antennas and Propagation (EuCAP 2017), Mar 2017, Paris, France. pp.84-87, 2017, 〈10.23919/EuCAP.2017.7928501〉
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https://hal.archives-ouvertes.fr/hal-01590190
Contributeur : Andrea Massa <>
Soumis le : mardi 19 septembre 2017 - 13:04:57
Dernière modification le : jeudi 26 avril 2018 - 17:21:45

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Lorenza Tenuti, Giacomo Oliveri, Daniele Bresciani, Andrea Massa. Advanced learning-based approaches for reflectarrays design. 11th European Conference on Antennas and Propagation (EuCAP 2017), Mar 2017, Paris, France. pp.84-87, 2017, 〈10.23919/EuCAP.2017.7928501〉. 〈hal-01590190〉

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