Automated Recovery of Compressedly Observed Sparse Signals From Smooth Background. Chen, Z., Molina, R., & Katsaggelos, A. K. IEEE Signal Processing Letters, 21(8):1012–1016, aug, 2014. ![Automated Recovery of Compressedly Observed Sparse Signals From Smooth Background [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex We propose a Bayesian based algorithm to recover sparse signals from compressed noisy measurements in the presence of a smooth background component. This problem is closely related to robust principal component analysis and compressive sensing, and is found in a number of practical areas. The proposed algorithm adopts a hierarchical Bayesian framework for modeling, and employs approximate inference to estimate the unknowns. Numerical examples demonstrate the effectiveness of the proposed algorithm and its advantage over the current state-of-the-art solutions. © 1994-2012 IEEE.
@article{Zhaofu2014a,
abstract = {We propose a Bayesian based algorithm to recover sparse signals from compressed noisy measurements in the presence of a smooth background component. This problem is closely related to robust principal component analysis and compressive sensing, and is found in a number of practical areas. The proposed algorithm adopts a hierarchical Bayesian framework for modeling, and employs approximate inference to estimate the unknowns. Numerical examples demonstrate the effectiveness of the proposed algorithm and its advantage over the current state-of-the-art solutions. {\textcopyright} 1994-2012 IEEE.},
author = {Chen, Zhaofu and Molina, Rafael and Katsaggelos, Aggelos K.},
chapter = {1012},
doi = {10.1109/LSP.2014.2321256},
isbn = {1070-9908 1558-2361},
issn = {1070-9908},
journal = {IEEE Signal Processing Letters},
keywords = {Bayesian algorithm,compressive sensing,robust principal component analysis},
month = {aug},
number = {8},
pages = {1012--1016},
title = {{Automated Recovery of Compressedly Observed Sparse Signals From Smooth Background}},
url = {http://ieeexplore.ieee.org/document/6808512/},
volume = {21},
year = {2014}
}
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