Analysis of Bivariate Coupling by Means of Recurrence

Christoph Bandt, Andreas Groth, Norbert Marwan, M Carmen Romano, Marco Thiel, Michael Carmen Rosenblum, Jurgen Kurths

Research output: Chapter in Book/Report/Conference proceedingChapter

8 Citations (Scopus)

Abstract

In the analysis of coupled systems, various techniques have been developed to model and detect dependencies from observed bivariate time series. Most well-founded methods, like Granger-causality and partial coherence, are based on the theory of linear systems: on correlation functions, spectra and vector autoregressive processes. In this paper we discuss a nonlinear approach using recurrence.
Original languageEnglish
Title of host publicationMathematical Methods in Signal Processing and Digital Image Analysis
EditorsRainer Dahlhaus, Jurgen Kurths, Peter Maass, Jens Timmer
Place of PublicationBerlin, Germany
PublisherSpringer Science+Business Media
Pages153-182
Number of pages30
ISBN (Electronic)978-3540756323
ISBN (Print)978-3540756316
DOIs
Publication statusPublished - 2008

Publication series

NameUnderstanding Complex Systems
PublisherSpringer Science+Business Media
Volume70
ISSN (Print)1860-0832

    Fingerprint

Cite this

Bandt, C., Groth, A., Marwan, N., Romano, M. C., Thiel, M., Rosenblum, M. C., & Kurths, J. (2008). Analysis of Bivariate Coupling by Means of Recurrence. In R. Dahlhaus, J. Kurths, P. Maass, & J. Timmer (Eds.), Mathematical Methods in Signal Processing and Digital Image Analysis (pp. 153-182). (Understanding Complex Systems; Vol. 70). Berlin, Germany: Springer Science+Business Media. https://doi.org/10.1007/978-3-540-75632-3_5