Higher and lower-order properties of the wavelet decomposition of self-similar processes

Author

Pesquet-Popescu, Beatrice ; Larzabal, Pascal

Author_Institution

L.E.Si.R.-E.N.S. de Cachan, France

fYear

1997

fDate

21-23 Jul 1997

Firstpage

458

Lastpage

462

Abstract

Self-similar processes have received increasing attention in the signal processing community, due to their wide applicability in modeling natural phenomena which exhibit “1/f” spectra and/or long-range dependence. On the other hand the wavelet decomposition became a very useful tool in describing nonstationary self-similar processes. In this paper we first investigate the existence and the properties of higher-order statistics of self-similar processes with finite variance. Then, we consider some self-similar processes with infinite variance and study the statistical properties of their wavelet coefficients

Keywords

higher order statistics; spectral analysis; wavelet transforms; 1/f spectra; finite variance; higher order properties; higher-order statistic; infinite variance; long-range dependence; lower-order properties; nonstationary self-similar processes; self-similar processes; signal processing; statistical properties; wavelet coefficients; wavelet decomposition; Analysis of variance; Brownian motion; Gaussian processes; Geophysics; Higher order statistics; Hydrology; Signal processing; Stochastic processes; Wavelet analysis; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Higher-Order Statistics, 1997., Proceedings of the IEEE Signal Processing Workshop on

Conference_Location

Banff, Alta.

Print_ISBN

0-8186-8005-9

Type

conf

DOI

10.1109/HOST.1997.613567

Filename

613567