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Proceedings Paper

Wavelets and related time-scale transforms
Author(s): Patrick Flandrin
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Paper Abstract

In a very recent past, new techniques, referred to as time-scale methods and making use of the so-called wavelet transform, have been proposed for the analysis of nonstationary or time-varying signals. They are basically devoted to the description of signal time evolutions at different observation scales; this is achieved by using shifted and dilated versions of some elementary analyzing waveform along the time axis. The purpose of this paper is twofold: it is intended (1) to provide a brief overview of linear wavelet techniques (continuous and discrete transforms) and bilinear time-scale methods (time-scale energy distributions), and (2) to put them in some common perspective with existing Signal Processing tools (Gabor decompositions, constant-Q analysis, quadrature mirror filters, wideband ambiguity functions, time-frequency energy distributions). Existing or potentially relevant applications are also pointed out.

Paper Details

Date Published: 1 November 1990
PDF: 12 pages
Proc. SPIE 1348, Advanced Signal Processing Algorithms, Architectures, and Implementations, (1 November 1990); doi: 10.1117/12.23458
Show Author Affiliations
Patrick Flandrin, LTS-ICPI (France)

Published in SPIE Proceedings Vol. 1348:
Advanced Signal Processing Algorithms, Architectures, and Implementations
Franklin T. Luk, Editor(s)

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