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Visualization of coupling in time series by order recurrence plots
1Ernst-Moritz-Arndt-University of Greifswald, Jahnstrasse 15a, 17487 Greifswald, Germany. groth@uni-greifswald.de
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 31, 2005
Summary
We present a novel method to visualize time series dependencies using cross recurrence plots and ordinal patterns. This approach yields a robust coupling strength measure, effective even with noisy or distorted data.
Area of Science:
- Complex systems analysis
- Nonlinear dynamics
- Time series analysis
Background:
- Understanding dependencies between time series is crucial in various scientific fields.
- Existing methods can be sensitive to noise, amplitude distortions, and trends.
Purpose of the Study:
- To introduce a new method for visualizing and quantifying dependencies between two time series.
- To develop a coupling measure robust against common data imperfections.
Main Methods:
- Application of cross recurrence plots to local ordinal patterns.
- Derivation of a coupling strength measure.
- Analysis of coupled Rössler systems.
- Testing on electroencephalogram (EEG) data.
Main Results:
- The method successfully visualizes time series dependencies.
- The derived coupling measure demonstrates robustness against noise, nonlinear distortions, and low-frequency trends.
- Phase coupling in Rössler systems was accurately determined.
- The method proved robust to artifacts in EEG data.
Conclusions:
- The proposed method offers a reliable way to analyze time series dependencies.
- The robustness of the coupling measure facilitates its application in real-world scenarios, including noisy biological signals.
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