Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries

Research output: Contribution to journalConference article in JournalResearchpeer-review

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Abstract

We generalize cyclic matching pursuit (CMP),
propose an orthogonal variant,
and examine their performance using multiscale time-frequency dictionaries
in the sparse approximation of signals.
Overall, we find that the cyclic approach of CMP
produces signal models that have a much lower approximation error
than existing greedy iterative descent methods
such as matching pursuit (MP),
and are competitive with models found using orthogonal MP (OMP),
and orthogonal least squares (OLS).
This implies that CMP is a strong alternative to
the more computationally complex approaches of OMP and OLS
for modeling high-dimensional signals.
Original languageEnglish
JournalAsilomar Conference on Signals, Systems and Computers. Conference Record
Pages (from-to)581-585
ISSN1058-6393
DOIs
Publication statusPublished - 2010
Event44th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, United States
Duration: 7 Nov 201010 Nov 2010

Conference

Conference44th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove
Period07/11/201010/11/2010

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Cite this

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title = "Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries",
abstract = "We generalize cyclic matching pursuit (CMP),propose an orthogonal variant,and examine their performance using multiscale time-frequency dictionariesin the sparse approximation of signals.Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation errorthan existing greedy iterative descent methodssuch as matching pursuit (MP),and are competitive with models found using orthogonal MP (OMP), and orthogonal least squares (OLS).This implies that CMP is a strong alternative to the more computationally complex approaches of OMP and OLSfor modeling high-dimensional signals.",
author = "Sturm, {Bob L.} and Christensen, {Mads Gr{\ae}sb{\o}ll}",
year = "2010",
doi = "10.1109/ACSSC.2010.5757627",
language = "English",
pages = "581--585",
journal = "Asilomar Conference on Signals, Systems and Computers. Conference Record",
issn = "1058-6393",
publisher = "I E E E Computer Society",

}

Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries. / Sturm, Bob L.; Christensen, Mads Græsbøll.

In: Asilomar Conference on Signals, Systems and Computers. Conference Record, 2010, p. 581-585.

Research output: Contribution to journalConference article in JournalResearchpeer-review

TY - GEN

T1 - Cyclic Matching Pursuits with Multiscale Time-frequency Dictionaries

AU - Sturm, Bob L.

AU - Christensen, Mads Græsbøll

PY - 2010

Y1 - 2010

N2 - We generalize cyclic matching pursuit (CMP),propose an orthogonal variant,and examine their performance using multiscale time-frequency dictionariesin the sparse approximation of signals.Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation errorthan existing greedy iterative descent methodssuch as matching pursuit (MP),and are competitive with models found using orthogonal MP (OMP), and orthogonal least squares (OLS).This implies that CMP is a strong alternative to the more computationally complex approaches of OMP and OLSfor modeling high-dimensional signals.

AB - We generalize cyclic matching pursuit (CMP),propose an orthogonal variant,and examine their performance using multiscale time-frequency dictionariesin the sparse approximation of signals.Overall, we find that the cyclic approach of CMP produces signal models that have a much lower approximation errorthan existing greedy iterative descent methodssuch as matching pursuit (MP),and are competitive with models found using orthogonal MP (OMP), and orthogonal least squares (OLS).This implies that CMP is a strong alternative to the more computationally complex approaches of OMP and OLSfor modeling high-dimensional signals.

U2 - 10.1109/ACSSC.2010.5757627

DO - 10.1109/ACSSC.2010.5757627

M3 - Conference article in Journal

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EP - 585

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

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

SN - 1058-6393

ER -