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Conference Papers Year : 2011

Soft Bayesian Pursuit Algorithm for Sparse Representations

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Abstract

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.
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Dates and versions

hal-00696898 , version 1 (14-05-2012)

Identifiers

  • HAL Id : hal-00696898 , version 1

Cite

Angélique Drémeau, Cedric Herzet, Laurent Daudet. Soft Bayesian Pursuit Algorithm for Sparse Representations. IEEE Workshop on Statistical Signal Processing, Jun 2011, Nice, France. ⟨hal-00696898⟩
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