Sparse signal recovery and acquisition with graphical models
Name
Indyk_Sparse signal recovery.pdf
Size
2.11 MB
Format
Adobe PDF
Checksum (MD5)
9780be6d244a266903a57b41c0a12f1f
Author(s)
Cevher, Volkan
Indyk, Piotr
Carin, Lawrence
Baraniuk, Richard G.
Date Issued
November 2010
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
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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/MSP.2010.938029
