Cross recurrence plot based synchronization of time series

By Norbert Marwan, Marco Thiel, N. Nowaczyk. 2002

287 citations recorded by the source corpus.

The method of recurrence plots is extended to the cross recurrence plots (CRP) which, among others, enables the study of synchronization or time differences in two time series. This is emphasized in a distorted main diagonal in the cross recurrence plot, the line of synchronization (LOS). A non-parametrical fit of this LOS can be used to rescale the time axis of the two data series (whereby one of them is compressed or stretched) so that they are synchronized. An application of this method to geophysical sediment core data illustrates its suitability for real data. The rock magnetic data of two different sediment cores from the Makarov Basin can be adjusted to each other by using this method, so that they are comparable.

Subfields: Economics and Econometrics, Molecular Biology, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b35ef07fbe390e0406c2ff4aecae8546ab07ed3c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Norbert Marwan
2. Jürgen Kurths
3. Yong Zou
4. Reik V. Donner
5. Jonathan F. Donges
6. M. Romano
7. M. Thiel
8. Cornelis J. Stam

In Molecular Biology

1. Jürgen Kurths
2. Jonathan F. Donges
3. Yong Zou
4. Reik V. Donner
5. Norbert Marwan
6. Michael Small

In Signal Processing

1. Norbert Marwan
2. Jürgen Kurths
3. Yong Zou
4. Jonathan F. Donges
5. Reik V. Donner

Citations in the corpus

• Complex network approaches to nonlinear time series analysis (2019, background): “been proposed [58]: cross-recurrence plots [97, 98, 189] and joint recurrence plots [99].”
• A historical review of recurrence plots (2008, methodology): “ 35]. Here delay based variants of the RQA measures were introduced [30]. Furthermore, CRPs appeared rather illustrative to study differences or transformations of time scales of similar observations [34]. This feature was later used to understand changing shapes of line structures in RPs [31]. The ”
• Influence of observational noise on the recurrence quantification analysis (2002, methodology): “The connection between RPs and RQA forms a powerful tool; both methods have been widely applied in many fields such as physics, medicine, earth science and economics [3] [6] [7] [9] [12].”
• Recurrence-based time series analysis by means of complex network methods (2010, methodology): “The study of recurrences by means of RPs has become popular with the introduction of recurrence quantification analysis (RQA) [Zbilut & Webber Jr., 1992; Marwan et al. , 2002b].”
• Encounters with neighbours : current developments of concepts based on recurrence plots and their applications (2003, methodology): “The difference between these measures and the traditional RQA measures is their ability to find transitions between chaos and chaos [Marwan et al., 2002].”
• Detection of changes in cracked aluminium plate determinism by recurrence analysis (2012, background): “Applications of the methods can be found in various research areas including: engineering [24–26], astrophysics [27, 28], biology [29], chemistry [30], geology [31], cardiology [32], neuroscience [33], and economy [34].”