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CoSaMP: iterative signal recovery from incomplete and inaccurate samples

Needell, Deanna and Tropp, Joel A. (2010) CoSaMP: iterative signal recovery from incomplete and inaccurate samples. Communications of the ACM, 53 (12). pp. 93-100. ISSN 0001-0782. https://resolver.caltech.edu/CaltechAUTHORS:20110201-090245482

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Abstract

Compressive sampling (CoSa) is a new paradigm for developing data sampling technologies. It is based on the principle that many types of vector-space data are compressible, which is a term of art in mathematical signal processing. The key ideas are that randomized dimension reduction preserves the information in a compressible signal and that it is possible to develop hardware devices that implement this dimension reduction efficiently. The main computational challenge in CoSa is to reconstruct a compressible signal from the reduced representation acquired by the sampling device. This extended abstract describes a recent algorithm, called CoSaMP, that accomplishes the data recovery task. It was the first known method to offer near-optimal guarantees on resource usage.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/1859204.1859229 DOIArticle
ORCID:
AuthorORCID
Needell, Deanna0000-0002-8058-8638
Tropp, Joel A.0000-0003-1024-1791
Additional Information:© 2010 ACM. The original version of this paper appeared in Applied and Computational Harmonic Analysis 26, 3 (2008), 301–321.
Subject Keywords:coding and information theory, mathematical software
Issue or Number:12
Record Number:CaltechAUTHORS:20110201-090245482
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20110201-090245482
Official Citation:Needell, D. and J. A. Tropp (2010). "CoSaMP: iterative signal recovery from incomplete and inaccurate samples." Commun. ACM 53(12): 93-100.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:21944
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:14 Feb 2011 17:37
Last Modified:14 Feb 2020 18:37

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