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Row-Action Methods for Compressed Sensing

Sra, Suvrit and Tropp, Joel A. (2006) Row-Action Methods for Compressed Sensing. In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2006), Toulouse, France, 14-19 May 2006. Vol.III. IEEE , Piscataway, NJ, III-868. ISBN 1-4244-0469-X. https://resolver.caltech.edu/CaltechAUTHORS:SRAicassp06

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Abstract

Compressed Sensing uses a small number of random, linear measurements to acquire a sparse signal. Nonlinear algorithms, such as l1minimization, are used to reconstruct the signal from the measured data. This paper proposes row-action methods as a computational approach to solving the l1optimization problem. This paper presents a specific row-action method and provides extensive empirical evidence that it is an effective technique for signal reconstruction. This approach offers several advantages over interior-point methods, including minimal storage and computational requirements, scalability, and robustness.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/ICASSP.2006.1660792DOIUNSPECIFIED
ORCID:
AuthorORCID
Tropp, Joel A.0000-0003-1024-1791
Additional Information:© Copyright 2006 IEEE. Reprinted with permission. [Posted online: 2006-07-24] JAT was supported by NSF DMS Grant No. 0503299.
Record Number:CaltechAUTHORS:SRAicassp06
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:SRAicassp06
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9066
Collection:CaltechAUTHORS
Deposited By: Archive Administrator
Deposited On:25 Oct 2007
Last Modified:02 Oct 2019 23:56

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