Abstract
Recent studies have shown that results deduced on the basis of a new time domain termed natural time reveal that novel dynamical features hidden behind time-series in complex systems can be uncovered. Here, we propose a method for estimating the multifractal behavior of time series by studying the fluctuations of natural time under time reversal. Examples of the application of this method to fractional Gaussian noises, fractional Brownian motions, binomial multifractal series, Lévy processes as well as interbeat intervals’ time series from electrocardiograms are presented.
| Original language | English |
|---|---|
| Pages (from-to) | 153-164 |
| Number of pages | 11 |
| Journal | Physica A: Statistical Mechanics and its Applications |
| Volume | 512 |
| Early online date | 4 Aug 2018 |
| DOIs | |
| Publication status | Published - Dec 2018 |
Bibliographical note
NOTICE: this is the author’s version of a work that was accepted for publication in Physica A: Statistical Mechanics and its Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Physica A: Statistical Mechanics and its Applications, VOL 512, (2018)] DOI: 10.1016/j.physa.2018.08.015© 2017, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
- Heart rate variability
- fBm
- Time reversal
- Natural time
- Multifractals
- fGn
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Stavros Christopoulos
- Complex Systems Honorary and Visiting Researchers - ICS Research Fellow
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