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Sparsity estimation from compressive projections via sparse random matrices
The aim of this paper is to develop strategies to estimate the sparsity degree of a signal from compressive projections, without the burden of recovery. We consider both the noise-free and the noisy settings, and we show how to extend the proposed framework to the case of non-exactly sparse signals....
Autores principales: | Ravazzi, Chiara, Fosson, Sophie, Bianchi, Tiziano, Magli, Enrico |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6414084/ https://www.ncbi.nlm.nih.gov/pubmed/30956656 http://dx.doi.org/10.1186/s13634-018-0578-0 |
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