Bayesian Pursuit Algorithm for Sparse Representation

Hadi Zayyani (1) , Massoud Babaie-Zadeh (1) , Christian Jutten (2)

1 EE department of SUT [Tehran] - Department of Electrical Engineering [Tehran]
2 GIPSA-SIGMAPHY - GIPSA - Signal Images Physique

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.

Keywords: Compressed Sensing (CS); Pursuit algorithms; Sparse Component Analysis (SCA); Sparse representation

Domains: Signal and Image Processing; Signal and Image processing

Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutten. Bayesian Pursuit Algorithm for Sparse Representation. ICASSP 2009 - IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2009, Taipei, Taiwan. pp.1549-1552. ⟨hal-00400478⟩