@inbook{87d81e344ffb420ea7673fd24076f590,
title = "Identifying coupling directions by recurrences",
abstract = "The identification of the coupling direction from measured time series taking place in a group of interacting components is an important challenge for many experimental studies. In Part I of this chapter, we introduce a method to detect and quantify the asymmetry of the coupling between two interacting systems based on their recurrence properties. This method can detect the direction of the coupling in weakly as well as strongly coupled systems. It even allows detecting the asymmetry of the coupling in the more challenging case of structurally different systems and it is very robust against noise. We also address the problem of detecting the asymmetry of the coupling in passive experiments, i.e., when the strength of the coupling cannot be systematically changed, which is of great relevance for the analysis of experimental time series. Part II of this chapter hinges on a generalisation of conditional probability of recurrence to the case of multivariate time series where indirect interactions might be present. We test our method by an example of three coupled Lorenz systems. Our results confirm that the proposed method has much potential to identify indirect coupling.",
author = "Yong Zou and Romano, {M Carmen} and Marco Thiel and J{\"u}rgen Kurths",
note = "Funding Details Number; Acronym; Sponsor: 11075056; NSFC; National Natural Science Foundation of China 11135001; NSFC; National Natural Science Foundation of China 11305062; NSFC; National Natural Science Foundation of China SRF; National Natural Science Foundation of China",
year = "2014",
month = aug,
day = "12",
doi = "10.1007/978-3-319-07155-8_3",
language = "English",
isbn = "9783319071541",
series = "Understanding Complex Systems",
publisher = "Springer-Verlag",
pages = "65--99",
editor = "{Webber Jr}, {Charles L} and Norbert Marwan",
booktitle = "Recurrence Quantification Analysis",
}