Multifractal Processes

Abstract

This paper has two main objectives. First, it develops the multifractal formalism in a context suitable for both, measures and functions, deterministic as well as random, thereby emphasizing an intuitive approach. Second, it carefully discusses several examples, such as the binomial cascades and self-similar processes with a special eye on the use of wavelets. Particular attention is given to a novel class of multifractal processes which combine the attractive features of cascades and self-similar processes. Statistical properties of estimators as well as modelling issues are addressed.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1999
Accession Number
ADA531331

Entities

People

  • Rudolf H. Riedi

Organizations

  • Rice University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Binomials
  • Brownian Motion
  • Computations
  • Distribution Functions
  • Ergodic Processes
  • Estimators
  • Gaussian Noise
  • Gaussian Processes
  • Normal Distribution
  • Order Statistics
  • Polynomials
  • Probability
  • Random Variables
  • Simulations
  • Statistics
  • Stochastic Processes
  • Wavelet Transforms

Readers

  • Neural Network Machine Learning.
  • Statistical inference.
  • Systems Analysis and Design