Abstract
AbstractThe last decade has witnessed a number of important and exciting developments that had been achieved for improving recurrence plot-based data analysis and to widen its application potential. We will give a brief overview about important and innovative developments, such as computational improvements, alternative recurrence definitions (event-like, multiscale, heterogeneous, and spatio-temporal recurrences) and ideas for parameter selection, theoretical considerations of recurrence quantification measures, new recurrence quantifiers (e.g. for transition detection and causality detection), and correction schemes. New perspectives have recently been opened by combining recurrence plots with machine learning. We finally show open questions and perspectives for futures directions of methodical research.
Funder
Deutsche Forschungsgemeinschaft
Potsdam-Institut für Klimafolgenforschung (PIK) e.V.
Publisher
Springer Science and Business Media LLC
Subject
Physical and Theoretical Chemistry,General Physics and Astronomy,General Materials Science
Cited by
10 articles.
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