DocumentCode :
1312886
Title :
Sparse Signal Recovery and Acquisition with Graphical Models
Author :
Cevher, Volkan ; Indyk, Piotr ; Carin, Lawrence ; Baraniuk, Richard G.
Volume :
27
Issue :
6
fYear :
2010
Firstpage :
92
Lastpage :
103
Abstract :
A great deal of theoretic and algorithmic research has revolved around sparsity view of signals over the last decade to characterize new, sub-Nyquist sampling limits as well as tractable algorithms for signal recovery from dimensionality reduced measurements. Despite the promising advances made, real-life applications require more realistic signal models that can capture the underlying, application-dependent order of sparse coefficients, better sampling matrices with information preserving properties that can be implemented in practical systems, and ever faster algorithms with provable recovery guarantees for real-time operation.
Keywords :
signal detection; signal sampling; sparse matrices; graphical models; sampling matrices; signal acquistion; sparse signal recovery; sub-Nyquist sampling; Algorithm design and analysis; Approximation algorithms; Approximation methods; Graphical models; Noise; Signal processing algorithms; Sparse matrices;
fLanguage :
English
Journal_Title :
Signal Processing Magazine, IEEE
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2010.938029
Filename :
5563109
Link To Document :
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