Recurrent Deep Learning for Beam Pattern Synthesis in Optimized Antenna Arrays

This work proposes and describes a deep learning-based approach utilizing recurrent neural networks (RNNs) for beam pattern synthesis considering uniform linear arrays. In this particular case, the deep neural network (DNN) learns from previously optimized radiation patterns as inputs and generates...

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Autores principales:	Armando Arce, Fernando Arce, Enrique Stevens-Navarro, Ulises Pineda-Rico, Marco Cardenas-Juarez, Abel Garcia-Barrientos
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2024-12-01
Colección:	Applied Sciences
Materias:	deep learning neural networks antenna arrays antenna radiation patterns synthesis optimization
Acceso en línea:	https://www.mdpi.com/2076-3417/15/1/204
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