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Sparse signal recovery and acquisition with graphical models

Author(s)
Cevher, Volkan; Indyk, Piotr; Carin, Lawrence; Baraniuk, Richard G.
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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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.
Date issued
2010-11
URI
http://hdl.handle.net/1721.1/71888
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
IEEE Signal Processing Magazine
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Cevher, Volkan et al. “Sparse Signal Recovery and Acquisition with Graphical Models.” IEEE Signal Processing Magazine (2010). © Copyright 2010 IEEE
Version: Final published version
ISSN
1053-5888

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