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

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=148323