Ordinal patterns in the Duffing oscillator: Analyzing powers of characterization
| Autor: | Arjendu K. Pattanayak, Andrés Aragoneses, Ivan Gunther |
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| Rok vydání: | 2021 |
| Předmět: |
J.2
Applied Mathematics Chaotic FOS: Physical sciences General Physics and Astronomy Parity of a permutation Duffing equation Statistical and Nonlinear Physics Probability and statistics Lyapunov exponent Nonlinear Sciences - Chaotic Dynamics Stability (probability) Nonlinear Sciences - Adaptation and Self-Organizing Systems Symmetry (physics) symbols.namesake Physics - Data Analysis Statistics and Probability symbols Entropy (information theory) Statistical physics Chaotic Dynamics (nlin.CD) Adaptation and Self-Organizing Systems (nlin.AO) Data Analysis Statistics and Probability (physics.data-an) Mathematical Physics Mathematics |
| Zdroj: | Chaos: An Interdisciplinary Journal of Nonlinear Science. 31:023104 |
| ISSN: | 1089-7682 1054-1500 |
| DOI: | 10.1063/5.0037999 |
| Popis: | Ordinal Patterns are a time-series data analysis tool used as a preliminary step to construct the Permutation Entropy which itself allows the same characterization of dynamics as chaotic or regular as more theoretical constructs such as the Lyapunov exponent. However ordinal patterns store strictly more information than Permutation Entropy or Lyapunov exponents. We present results working with the Duffing oscillator showing that ordinal patterns reflect changes in dynamical symmetry invisible to other measures, even Permutation Entropy. We find that these changes in symmetry at given parameter values are correlated with a change in stability at neighboring parameters which suggests a novel predictive capability for this analysis technique. 8 pages, 9 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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