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Improved iterative shrinkage-thresholding for sparse signal recovery via Laplace mixtures models

In this paper, we propose a new method for support detection and estimation of sparse and approximately sparse signals from compressed measurements. Using a double Laplace mixture model as the parametric representation of the signal coefficients, the problem is formulated as a weighted ℓ(1) minimiza...

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Detalles Bibliográficos
Autores principales: Ravazzi, Chiara, Magli, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6434991/
https://www.ncbi.nlm.nih.gov/pubmed/30996728
http://dx.doi.org/10.1186/s13634-018-0565-5