Wavelets and related time-scale transforms
Patrick Flandrin · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
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.