Estimation of the self-similarity parameter using the wavelet transform

Authors:
S. Soltani;P. Simard;D. Boichu
Affiliations:
Laboratoire HEUDIASYC U.M.R., C.N.R.S. 6599, Université de Technologie de Compiègne, B.P. 20529, 60205 Compiègne Cedex, France;Laboratoire HEUDIASYC U.M.R., C.N.R.S. 6599, Université de Technologie de Compiègne, B.P. 20529, 60205 Compiègne Cedex, France;Laboratoire de Mathématiques Appliquées, Université de Technologie de Compiègne, B.P. 20529, 60205 Compiègne Cedex, France
Venue:
Signal Processing
Year:
2004

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Abstract

We are interested in analyzing fBm self-similar processes and particularly in estimating the parameter that tunes the trajectories regularity. The proposed method uses the wavelet coefficients and their scale invariance property to reduce the problem into a linear regression estimation one. Results on simulated data are shown to substantiate our approach.