An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint
TRAONMILIN, Yann
Centre National de la Recherche Scientifique [CNRS]
Institut de Mathématiques de Bordeaux [IMB]
Centre National de la Recherche Scientifique [CNRS]
Institut de Mathématiques de Bordeaux [IMB]
TRAONMILIN, Yann
Centre National de la Recherche Scientifique [CNRS]
Institut de Mathématiques de Bordeaux [IMB]
< Réduire
Centre National de la Recherche Scientifique [CNRS]
Institut de Mathématiques de Bordeaux [IMB]
Langue
en
Communication dans un congrès
Ce document a été publié dans
in Proceedings of iTWIST'20, Paper-ID: 7, Nantes, France, December, 2-4, 2020, 2020-12-02, Nantes.
Résumé en anglais
Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a practical algorithm to minimize the corresponding ...Lire la suite >
Theoretical results show that sparse off-the-grid spikes can be estimated from (possibly compressive) Fourier measurements under a minimum separation assumption. We propose a practical algorithm to minimize the corresponding non-convex functional based on a projected gradient descent coupled with an initialization procedure. We give qualitative insights on the theoretical foundations of the algorithm and provide experiments showing its potential for imaging problems.< Réduire
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