On the Complementarity of Sparse L0 and CEL0 Regularized Loss Landscapes for DOA Estimation

L0 sparse methods are not widespread in Direction-Of-Arrival (DOA) estimation yet, despite their potential superiority over classical methods in difficult scenarios. This comes from the difficulties encountered for global optimization on hill-climbing error surfaces. In this paper, we explore the lo...

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Detalles Bibliográficos
Autores principales: Delmer, Alice, Ferréol, Anne, Larzabal, Pascal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468343/
https://www.ncbi.nlm.nih.gov/pubmed/34577284
http://dx.doi.org/10.3390/s21186081

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8468343/
https://www.ncbi.nlm.nih.gov/pubmed/34577284
http://dx.doi.org/10.3390/s21186081

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