A practical comparison of fBm estimators

G. Jacquet, R. Harba, A. Flores, L. Vilcahuaman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Wavelet estimator of the H parameter for fractional Brownian motion (fBm) is the most interesting one from a theoretical point of view. Indeed, Wavelet estimates are asymptotically efficient and has a complexity in only O(N). However, on limited time signals, the efficiency is not proved. In addition, some corrections have to be performed to maintain high performances. As a result, the complexity of the wavelet estimator increases so that other estimators can be thought of. In this paper, we are comparing wavelet estimator to maximum likelihood ones (classical and Whittle type) which both have also interesting theoretical properties. Results show that Whittle ML estimator is the best in terms of performances and complexity.

Original languageEnglish
Title of host publicationICSP2010 - 2010 IEEE 10th International Conference on Signal Processing, Proceedings
Pages183-186
Number of pages4
DOIs
StatePublished - 2010
Event2010 IEEE 10th International Conference on Signal Processing, ICSP2010 - Beijing, China
Duration: 24 Oct 201028 Oct 2010

Publication series

NameInternational Conference on Signal Processing Proceedings, ICSP

Conference

Conference2010 IEEE 10th International Conference on Signal Processing, ICSP2010
Country/TerritoryChina
CityBeijing
Period24/10/1028/10/10

Keywords

  • Estimators
  • Fractal
  • Maximum Likelihood
  • Wavelets

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