Compressed sensing with coherent and redundant dictionaries-Reference-Cited by-同舟云学术

Compressed sensing with coherent and redundant dictionaries

Published:2011-07 Issue:1 Volume:31 Page:59-73
ISSN:1063-5203
Container-title:Applied and Computational Harmonic Analysis
language:en
Short-container-title:Applied and Computational Harmonic Analysis

Author:

Candès Emmanuel J.,Eldar Yonina C.,Needell Deanna,Randall Paige

Publisher

Elsevier BV

Subject

Applied Mathematics

Reference42 articles.

1. Bootstrap methods in signal processing;Zoubir;IEEE Signal Process. Mag.,2007

2. Sensing, sampling, and compression;Baraniuk;IEEE Signal Process. Mag.,2008

3. The fast Johnson–Lindenstrauss transform and approximate nearest neighbors;Ailon;SIAM J. Comput.,2009

4. N. Ailon, E. Liberty, An almost optimal unrestricted fast Johnson–Lindenstrauss transform, in: ACM-SIAM Symposium on Discrete Algorithms, 2011.

5. W. Bajwa, R. Calderbank, S. Jafarpour, Why Gabor frames? Two fundamental measures of coherence and their geometric significance, IEEE Trans. Signal Process. (2008), in press.

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