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CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (2008)
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| Venue: | California Institute of Technology, Pasadena |
| Citations: | 763 - 13 self |
BibTeX
@TECHREPORT{Needell08cosamp:iterative,
author = {D. Needell and J. A. Tropp},
title = {CoSaMP: Iterative signal recovery from incomplete and inaccurate samples},
institution = {California Institute of Technology, Pasadena},
year = {2008}
}
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Abstract
Abstract. Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling is to approximate a compressible signal from noisy samples. This paper describes a new iterative recovery algorithm called CoSaMP that delivers the same guarantees as the best optimization-based approaches. Moreover, this algorithm offers rigorous bounds on computational cost and storage. It is likely to be extremely efficient for practical problems because it requires only matrix–vector multiplies with the sampling matrix. For compressible signals, the running time is just O(N log 2 N), where N is the length of the signal. 1.
Keyphrases
iterative signal recovery inaccurate sample compressible signal practical problem new paradigm optimization-based approach noisy sample orthonormal basis compressive sampling new iterative recovery algorithm major algorithmic challenge rigorous bound computational cost running time matrix vector multiplies
