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Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit

Joel A. Tropp; Anna C. Gilbert · IEEE Transactions on Information Theory · 2007

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<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> This paper demonstrates theoretically and empirically that a greedy algorithm called Orthogonal Matching Pursuit (OMP) can reliably recover a signal with <emphasis><formula formulatype="inline"><tex>$m$</tex></formula></emphasis> nonzero entries in dimension <emphasis><formula formulatype="inline"><tex>$d$</tex> </formula></emphasis> given <emphasis><formula formulatype="inline"><tex>$ {\rm O}(m \ln d)$</tex></formula></emphasis> random linear measurements of that signal. This is a massive improvement over previous results, which require <emphasis><formula formulatype="inline"><tex>${\rm O}(m^{2})$</tex></formula></emphasis> measurements. The new results for OMP are comparable with recent results for another approach called Basis Pursuit (BP). In some settings, the OMP algorithm is faster and easier to implement, so it is an attractive alternative to BP for signal recovery problems. </para>

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APA 7

Tropp, J. A. & Gilbert, A. C. (2007). Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit. https://doi.org/10.1109/tit.2007.909108

MLA

Tropp, Joel A, and Anna C. Gilbert. "Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit." 2007. https://doi.org/10.1109/tit.2007.909108.

Chicago

Tropp, Joel A. and Anna C. Gilbert. 2007. "Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit.". https://doi.org/10.1109/tit.2007.909108.

Harvard

Tropp, J. A. and Gilbert, A. C. 2007, Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit, IEEE Transactions on Information Theory, available at: https://doi.org/10.1109/tit.2007.909108 [Accessed 7 Aug. 2026].

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Title
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
Author / contributors
Joel A. Tropp; Anna C. Gilbert
Publisher
IEEE Transactions on Information Theory
Publication year
2007
Language
English

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