1 July 1994 Adaptive time-frequency decompositions
Author Affiliations +
Optical Engineering, 33(7), (1994). doi:10.1117/12.173207
Abstract
Computing the optimal expansion of a signal in a redundant dictionary of waveforms is an NP-hard problem. We introduce a greedy algorithm, called a matching pursuit, which computes a suboptimal expansion. The dictionary waveforms that best match a signal's structures are chosen iteratively. An orthogonalized version of the matching pursuit is also developed. Matching pursuits are general procedures for computing adaptive signal representations. With a dictionary of Gabor functions, a matching pursuit defines an adaptive time-frequency transform. Matching pursuits are chaotic maps whose attractors define a generic noise with respect to the dictionary. We derive an algorithm that isolates the coherent structures of a signal and describe an application to pattern extraction from noisy signals.
Geoffrey M. Davis, Stephane G. Mallat, Zhifeng Zhang, "Adaptive time-frequency decompositions," Optical Engineering 33(7), (1 July 1994). http://dx.doi.org/10.1117/12.173207
JOURNAL ARTICLE
9 PAGES


SHARE
KEYWORDS
Associative arrays

Time-frequency analysis

Chemical species

Rutherfordium

Signal to noise ratio

Radon

Interference (communication)

RELATED CONTENT


Back to Top