Maximum likelihood estimation of the fractal dimensions of stochastic fractals and Cramer-Rao bounds

  • Ahmed H. Tewfik*
  • , Mohamed Deriche
  • *Corresponding author for this work

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

4 Scopus citations

Abstract

A maximum likelihood (ML) estimator for the parameters of Gaussian versions of the fractionally differenced white-noise process is developed. A closed-form expression for the likelihood equation is given, and Cramer-Rao bounds are computed for finite-size sample data sets. It is shown how the theory can be extended to the case where the fractionally differenced white-noise process is observed in the presence of white noise. The results obtained with this ML approach are satisfactory, with a mean square error which is very close to the theoretically computed Cramer-Rao bound.

Original languageEnglish
Title of host publicationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
PublisherPubl by IEEE
Pages3381-3384
Number of pages4
ISBN (Print)078030033
StatePublished - 1991

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume5
ISSN (Print)0736-7791

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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