NMF-based sparse unmixing of complex mixtures
Résumé
In this work, we are interested in unmixing complex mixtures based on Nuclear Magnetic Resonance spectroscopy spectra. More precisely, we propose to solve a 2D blind source separation problem where signals (spectra) are highly sparse. The separation is formulated as a nonnegative matrix factorization problem that is solved using a block coordinate proximal gradient algorithm involving various sparse regularizations. An application to 2D NMR HSQC experience is presented and shows the good performances of the proposed method.
Origine : Fichiers produits par l'(les) auteur(s)
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