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Communication Dans Un Congrès Année : 2010

Bayesian Pursuit Algorithms

Résumé

This paper addresses the sparse representation (SR) problem within a general Bayesian framework. We show that the Lagrangian formulation of the standard SR problem can be regarded as a limit case of a general maximum a posteriori (MAP) problem involving Bernoulli-Gaussian variables. We then propose different tractable implementations of this MAP problem and explain several well-known pursuit algorithms (e.g., MP, OMP, StOMP, CoSaMP, SP) as particular cases of the proposed Bayesian formulation.
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Dates et versions

inria-00539109 , version 1 (24-11-2010)

Identifiants

  • HAL Id : inria-00539109 , version 1

Citer

Cédric Herzet, Angélique Drémeau. Bayesian Pursuit Algorithms. Proc. European Signal Processing Conference (EUSIPCO), Aug 2010, Aalborg, Denmark. ⟨inria-00539109⟩
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