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Synchronization Analysis of Bivariate Time Series and Its Application to Medical Data

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Medical Data Analysis (ISMDA 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1933))

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Abstract

A typical problem in time series analysis is to reveal the presence of an interdependence between two (or more) signals. Such an analysis is traditionally done by means of cross-correlation (cross-spectrum) techniques or nonlinear statistical measures.

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References

  1. Rosenblum, M.G., Pikovsky, A.S., Schäfer, C., Tass, P., Kurths, J.: Phase Synchronization: From Theory to Data Analysis. to appear in: Handbook of Biological Physics, Elsevier Science, Series Editor A.J. Hoff, Vol. 4, Neuro-informatics, Editors: S. Gielen and F. Moss

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Author information

Authors and Affiliations

  1. Potsdam University, Germany

    M. Rosenblum

Authors
  1. M. Rosenblum
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Editor information

Editors and Affiliations

  1. Fachbereich Biologie und Informatik AG Adaptive Systemarchitektur, Johann Wolfgang Goethe-Universität, Robert-Mayer-Str. 11-15, 60054, Frankfurt a.M., Germany

    Rüdiger W. Brause

  2. Klinik für Allgemein- und Gefässchirurgie, Johann Wolfgang Goethe-Universität, Theodor-Stern-Kai 7, 60590, Frankfurt a.M., Germany

    Ernst Hanisch

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© 2000 Springer-Verlag Berlin Heidelberg

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Rosenblum, M. (2000). Synchronization Analysis of Bivariate Time Series and Its Application to Medical Data. In: Brause, R.W., Hanisch, E. (eds) Medical Data Analysis. ISMDA 2000. Lecture Notes in Computer Science, vol 1933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39949-6_3

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  • DOI: https://doi.org/10.1007/3-540-39949-6_3

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-41089-8

  • Online ISBN: 978-3-540-39949-0

  • eBook Packages: Springer Book Archive

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