Extending multifractal analysis to negative regularity: p-exponents and p-leaders
Scale invariance is a widely used concept to analyze real-world data from many different
applications and multifractal analysis has become the standard corresponding signal …
applications and multifractal analysis has become the standard corresponding signal …
p-exponent and p-leaders, Part I: Negative pointwise regularity
Multifractal analysis aims to characterize signals, functions, images or fields, via the
fluctuations of their local regularity along time or space, hence capturing crucial features of …
fluctuations of their local regularity along time or space, hence capturing crucial features of …
p-exponent and p-leaders, Part II: Multifractal analysis. Relations to detrended fluctuation analysis
Multifractal analysis studies signals, functions, images or fields via the fluctuations of their
local regularity along time or space, which capture crucial features of their temporal/spatial …
local regularity along time or space, which capture crucial features of their temporal/spatial …
Finite-Resolution Effects in -Leader Multifractal Analysis
Multifractal analysis has become a standard signal processing tool, for which a promising
new formulation, the pleader multifractal formalism, has recently been proposed. It relies on …
new formulation, the pleader multifractal formalism, has recently been proposed. It relies on …
Extreme values, heavy tails and linearization effect: A contribution to empirical multifractal analysis
Multifractal analysis is becoming a standard tool in signal processing commonly involved in
classical tasks such as detection, estimation or identification. Essentially, in practice, it …
classical tasks such as detection, estimation or identification. Essentially, in practice, it …
Multifractal analysis of self-similar processes
Scale invariance and multifractal analysis are nowadays widely used in applications. For
modeling scale invariance in data, two classes of processes are classically in competition …
modeling scale invariance in data, two classes of processes are classically in competition …
Bootstrap tests for the time constancy of multifractal attributes
On open and controversial issue in empirical data analysis is to decide whether scaling and
multifractal properties observed in empirical data actually exist, or whether they are induced …
multifractal properties observed in empirical data actually exist, or whether they are induced …
A Bayesian approach for the joint estimation of the multifractality parameter and integral scale based on the Whittle approximation
Multifractal analysis is a powerful tool used in signal processing. Multifractal models are
essentially characterized by two parameters, the multifractality parameter c 2 and the …
essentially characterized by two parameters, the multifractality parameter c 2 and the …
Bayesian estimation for the multifractality parameter
Multifractal analysis has matured into a widely used signal and image processing tool. Due
to the statistical nature of multifractal processes (strongly non-Gaussian and intricate …
to the statistical nature of multifractal processes (strongly non-Gaussian and intricate …
Bivariate multifractal analysis for non-homogenous point processes, with application to geospatial data
Multifractal analysis has become an important procedure for estimating local regularities in
experimental data. However, while univariate multifractal analysis is well-established, how …
experimental data. However, while univariate multifractal analysis is well-established, how …