| Metadato | Etiqueta | Valor | Idioma |
|---|---|---|---|
| dc.contributor.author | Autor | Angelosante, Daniele | es |
| dc.contributor.author | Autor | Bazerque, Juan Andrés | es |
| dc.contributor.author | Autor | Giannakis, Georgios B | es |
| dc.date.accessioned | Fecha ingreso | 2023-08-01T20:33:06Z | - |
| dc.date.available | Fecha disponible | 2023-08-01T20:33:06Z | - |
| dc.date.issued | Año de publicación | 2009 | es |
| dc.date.submitted | Fecha de subida | 20230801 | es |
| dc.description.abstract | Resumen | Two low-complexity sparsity-aware recursive schemes are developed for real-time adaptive signal processing. Both rely on a novel online coordinate descent algorithm which minimizes a time-weighted least-squares cost penalized with the scaled lscr1 norm of the unknown parameters. In addition to computational savings offered when processing time-invariant sparse parameter vectors, both schemes can be used for tracking slowly varying sparse signals. Analysis and preliminary simulations confirm that when the true signal is sparse the proposed estimators converge to a time-weighted least-absolute shrinkage and selection operator, and both outperform sparsity-agnostic recursive least-squares alternatives | es |
| dc.identifier.citation | Citación | Angelosante, D, Bazerque, J, Giannakis, G. “Online coordinate descent for adaptive estimation of sparse signals”. 15Th Workshop on Statistical Signal Processing, Cardiff, UK, 2009.. doi: 10.1109/SSP.2009.5278561 | es |
| dc.identifier.doi | DOI | doi: 10.1109/SSP.2009.5278561 | es |
| dc.identifier.uri | URI | https://hdl.handle.net/20.500.12008/38633 | - |
| dc.language | metadata.dc.language | en | es |
| dc.publisher | Editorial | IEEE | es |
| dc.relation.ispartof | EN | 15th Workshop on Statistical Signal Processing, Cardiff, UK, 2009. | es |
| dc.rights | Derechos | Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad De La República. (Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014) | es |
| dc.rights.licence | Licencia | Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) | es |
| dc.subject.other | Descriptores | Sistemas y Control | es |
| dc.title | Título | Online coordinate descent for adaptive estimation of sparse signals | es |
| dc.type | Tipo de documento | Ponencia | es |
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
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| ABG09.pdf | — | 159.21 KB | Adobe PDF |