Trends in recurrence analysis of dynamical systems

被引:24
|
作者
Marwan, Norbert [1 ,2 ]
Kraemer, K. Hauke [1 ]
机构
[1] Leibniz Assoc, Potsdam Inst Climate Impact Res PIK, Telegrafenberg A31, D-14473 Potsdam, Germany
[2] Univ Potsdam, Inst Geosci, Karl Liebknecht Str 32, D-14476 Potsdam, Germany
来源
关键词
TIME-SERIES; QUANTIFICATION ANALYSIS; SPACE RECONSTRUCTION; EMBEDDING DIMENSION; DRIVING FORCES; PLOT; NETWORK; ENTROPY; CLASSIFICATION; DETERMINISM;
D O I
10.1140/epjs/s11734-022-00739-8
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
The 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.
引用
收藏
页码:5 / 27
页数:23
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