DocumentCode :
148323
Title :
Recovery of correlated sparse signals from under-sampled measurements
Author :
Zhaofu Chen ; Molina, Rafael ; Katsaggelos, Aggelos K.
Author_Institution :
Electr. Eng. & Comput. Sci. Dept., Northwestern Univ., Evanston, IL, USA
fYear :
2014
fDate :
1-5 Sept. 2014
Firstpage :
451
Lastpage :
455
Abstract :
In this paper we consider the problem of recovering temporally smooth or correlated sparse signals from a set of undersampled measurements. We propose two algorithmic solutions that exploit the signal temporal properties to improve the reconstruction accuracy. The effectiveness of the proposed algorithms is corroborated with experimental results.
Keywords :
compressed sensing; signal reconstruction; correlated sparse signal recovery; reconstruction accuracy; signal temporal properties; under-sampled measurements; Bayes methods; Cost function; Greedy algorithms; Image reconstruction; Noise measurement; Signal to noise ratio; Sparse signal recovery; convex relaxation method; greedy algorithm; multiple measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon
Type :
conf
Filename :
6952109
Link To Document :
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