Bayesian Pursuit Algorithm for Sparse Representation

Abstract : In this paper, we propose a Bayesian Pursuit algorithm for sparse representation. It uses both the simplicity of the pursuit algorithms and optimal Bayesian framework to determine active atoms in sparse representation of a signal. We show that using Bayesian Hypothesis testing to determine the active atoms from the correlations leads to an efficient activity measure. Simulation results show that our suggested algorithm has better performance among the algorithms which have been implemented in our simulations in most of the cases.
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Contributor : Christian Jutten <>
Submitted on : Tuesday, June 30, 2009 - 6:59:23 PM
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Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutten. Bayesian Pursuit Algorithm for Sparse Representation. IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2008, Apr 2009, Taipei, Taiwan. pp.1549-1552. ⟨hal-00400478⟩



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