Trends in recurrence analysis of dynamical systems
arXiv:2409.04110 · doi:10.1140/epjs/s11734-022-00739-8
Abstract
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.
34 pages, 14 figures, 1 table
References in corpus (13)
- Nonlinear time-series analysis revisited
- Recurrence plot statistics and the effect of embedding
- Analytical framework for recurrence-network analysis of time series
- Generalised Recurrence Plot Analysis for Spatial Data
- Geometric detection of coupling directions by means of inter-system recurrence networks
- PyRQA -- Conducting Recurrence Quantification Analysis on Very Long Time Series Efficiently
- Detecting recurrence domains of dynamical systems by symbolic dynamics
- Optimal reconstruction of dynamical systems: A noise amplification approach
- Radius selection using kernel density estimation for the computation of nonlinear measures
- Averaged Recurrence Quantification Analysis -- Method omitting the recurrence threshold choice
- Transformation cost spectrum for irregularly sampled time series
- Extended generalized recurrence plot quantification of complex circular patterns
- Visualizing driving forces of spatially extended systems using the recurrence plot framework