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Matching Pursuit and Atomic Signal Models Based on Recursive Filter Banks (1902)
| Venue: | IEEE Transactions on Signal Processing |
| Citations: | 45 - 1 self |
BibTeX
@ARTICLE{Goodwin02matchingpursuit,
author = {Michael M Goodwin and Martin Vetterli},
title = {Matching Pursuit and Atomic Signal Models Based on Recursive Filter Banks},
journal = {IEEE Transactions on Signal Processing},
year = {1902},
volume = {47},
pages = {1890--1902}
}
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Abstract
The matching pursuit algorithm can be used to derive signal decompositions in terms of the elements of a dictionary of time-frequency atoms. Using a structured overcomplete dictionary yields a signal model that is both parametric and signal-adaptive. In this paper, we apply matching pursuit to the derivation of signal expansions based on damped sinusoids. It is shown that expansions in terms of complex damped sinusoids can be efficiently derived using simple recursive filter banks. We discuss a subspace extension of the pursuit algorithm which provides a framework for deriving real-valued expansions of real signals based on such complex atoms. Furthermore, we consider symmetric and asymmetric two-sided atoms constructed from underlying one-sided damped sinusoids. The primary concern is the application of this approach to the modeling of signals with transient behavior such as music; it is shown that time-frequency atoms based on damped sinusoids are more suitable for representing trans...
Keyphrases
recursive filter bank atomic signal model pursuit algorithm damped sinusoid time-frequency atom asymmetric two-sided atom primary concern transient behavior complex atom one-sided damped sinusoid derive signal decomposition simple recursive filter bank signal model subspace extension complex damped sinusoid signal expansion structured overcomplete dictionary yield real signal real-valued expansion
