Stochastic Models That Separate Fractal Dimension and the Hurst Effect
Abstract
Fractal behavior and long-range dependence have been observed in an astonishing number of physical systems. Either phenomenon has been modeled by self-similar random functions, thereby implying a linear relationship between fractal dimension, a measure of roughness, and Hurst coefficient, a measure of long-memory dependence. This letter introduces simple stochastic models which allow for any combination of fractal dimension and Hurst exponent. We synthesize images from these models, with arbitrary fractal properties and power-law correlations, and propose a test for self-similarity.
- Publication:
-
SIAM Review
- Pub Date:
- January 2004
- DOI:
- 10.1137/S0036144501394387
- arXiv:
- arXiv:physics/0109031
- Bibcode:
- 2004SIAMR..46..269G
- Keywords:
-
- Cauchy class;
- fractal dimension;
- fractional Brownian motion;
- Hausdorff dimension;
- Hurst coefficient;
- long-range dependence;
- power-law covariance;
- self-similar;
- simulation;
- Physics - Data Analysis;
- Statistics and Probability;
- Mathematics - Probability;
- Nonlinear Sciences - Chaotic Dynamics
- E-Print:
- 8 pages, 2 figures