Cyclic Pure Greedy Algorithms for Recovering Compressively Sampled Sparse Signals

Bob L. Sturm; Mads Græsbøll Christensen; Remi Gribonval

doi:10.1109/ACSSC.2011.6190193

Cyclic Pure Greedy Algorithms for Recovering Compressively Sampled Sparse Signals

Bob L. Sturm, Mads Græsbøll Christensen, Remi Gribonval

Institut for Arkitektur og Medieteknologi

Publikation: Bidrag til tidsskrift › Konferenceartikel i tidsskrift › Forskning › peer review

11 Citationer (Scopus)

374 Downloads (Pure)

Abstract

The pure greedy algorithms
matching pursuit (MP) and complementary MP (CompMP)
are extremely computationally simple,
but can perform poorly in solving the linear inverse problems posed by
the recovery of compressively sampled sparse signals.
We show that by applying a cyclic minimization principle,
the performance of both are significantly improved
while remaining computationally simple.
Our simulations show that while MP and CompMP
may not be competitive with state-of-the-art recovery algorithms,
their cyclic variations are.
We discuss ways in which their complexity can be further reduced,
but our simulations show these can hurt recovery performance.
Finally, we derive the exact recovery condition of CompMP and both cyclic algorithms.

Originalsprog	Engelsk
Tidsskrift	Asilomar Conference on Signals, Systems and Computers. Conference Record
Sider (fra-til)	1143-1147
Antal sider	5
ISSN	1058-6393
DOI	https://doi.org/10.1109/ACSSC.2011.6190193
Status	Udgivet - 2011
Begivenhed	Asilomar Conference on Signals, Systems and computers, Nov. 6-9, 2011 - Pacific Grove, USA Varighed: 6 nov. 2011 → 9 nov. 2011

Seminar

Seminar	Asilomar Conference on Signals, Systems and computers, Nov. 6-9, 2011
Land/Område	USA
By	Pacific Grove
Periode	06/11/2011 → 09/11/2011

Adgang til dokumentet

10.1109/ACSSC.2011.6190193

Final versionAccepteret manuskript, 386 KB

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6190193

AUB Link

Søg efter materialet i Aalborg Universitetsbiblioteks søgemaskine

Cyclic matching pursuit for audio signal processing and recovery from compressed sensing
Sturm, B. L., Christensen, M. G. & Gribonval, R.
French Ambassador to Denmark, C. W. Obel's foundation
06/06/2011 → 24/06/2011
Projekter: Projekt › Forskning

Citationsformater

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title = "Cyclic Pure Greedy Algorithms for Recovering Compressively Sampled Sparse Signals",

abstract = "The pure greedy algorithmsmatching pursuit (MP) and complementary MP (CompMP)are extremely computationally simple, but can perform poorly in solving the linear inverse problems posed by the recovery of compressively sampled sparse signals.We show that by applying a cyclic minimization principle,the performance of both are significantly improvedwhile remaining computationally simple.Our simulations show that while MP and CompMP may not be competitive with state-of-the-art recovery algorithms,their cyclic variations are.We discuss ways in which their complexity can be further reduced,but our simulations show these can hurt recovery performance.Finally, we derive the exact recovery condition of CompMP and both cyclic algorithms.",

author = "Sturm, {Bob L.} and Christensen, {Mads Gr{\ae}sb{\o}ll} and Remi Gribonval",

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AU - Sturm, Bob L.

AU - Christensen, Mads Græsbøll

AU - Gribonval, Remi

PY - 2011

Y1 - 2011

N2 - The pure greedy algorithmsmatching pursuit (MP) and complementary MP (CompMP)are extremely computationally simple, but can perform poorly in solving the linear inverse problems posed by the recovery of compressively sampled sparse signals.We show that by applying a cyclic minimization principle,the performance of both are significantly improvedwhile remaining computationally simple.Our simulations show that while MP and CompMP may not be competitive with state-of-the-art recovery algorithms,their cyclic variations are.We discuss ways in which their complexity can be further reduced,but our simulations show these can hurt recovery performance.Finally, we derive the exact recovery condition of CompMP and both cyclic algorithms.

AB - The pure greedy algorithmsmatching pursuit (MP) and complementary MP (CompMP)are extremely computationally simple, but can perform poorly in solving the linear inverse problems posed by the recovery of compressively sampled sparse signals.We show that by applying a cyclic minimization principle,the performance of both are significantly improvedwhile remaining computationally simple.Our simulations show that while MP and CompMP may not be competitive with state-of-the-art recovery algorithms,their cyclic variations are.We discuss ways in which their complexity can be further reduced,but our simulations show these can hurt recovery performance.Finally, we derive the exact recovery condition of CompMP and both cyclic algorithms.

U2 - 10.1109/ACSSC.2011.6190193

DO - 10.1109/ACSSC.2011.6190193

M3 - Conference article in Journal

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EP - 1147

JO - Asilomar Conference on Signals, Systems and Computers. Conference Record

JF - Asilomar Conference on Signals, Systems and Computers. Conference Record

T2 - Asilomar Conference on Signals, Systems and computers, Nov. 6-9, 2011

Y2 - 6 November 2011 through 9 November 2011

ER -

Cyclic Pure Greedy Algorithms for Recovering Compressively Sampled Sparse Signals

Abstract

Seminar

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AUB Link

Fingeraftryk

Projekter

Cyclic matching pursuit for audio signal processing and recovery from compressed sensing

Citationsformater