Open AccessDetecting chaos in time series
Author(s) -
Vladimir Nikiforov,
S B Morgunova
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1683/2/022014
Subject(s) - chaos (operating system) , attractor , chaotic , series (stratigraphy) , lorenz system , computer science , time series , rössler attractor , statistical physics , mathematics , artificial intelligence , physics , machine learning , mathematical analysis , geology , computer security , paleontology
The method to detect the chaotic nature of a time series is proposed. The algorithm works well for known chaotic systems like the Lorenz attractor.