Soft Bayesian Pursuit Algorithm for Sparse Representations
Résumé
This paper deals with sparse representations within a Bayesian framework. For a Bernoulli-Gaussian model, we here propose a method based on a mean-field approximation to estimate the support of the signal. In numerical tests involving a recovery problem, the resulting algorithm is shown to have good performance over a wide range of sparsity levels, compared to various state-of-the-art algorithms.
Origine | Fichiers produits par l'(les) auteur(s) |
---|
Loading...