Nonlinear Time Series Analysis

Very short: The theories and results about Chaos are applied to time series like ECGs, EEGs, economical data etc.

Publications:

A. Schmitz, Measuring statistical dependence and coupling of subsystems , Phys. Rev. E 62, 7508 (2000)
T. Schreiber and A. Schmitz Surrogate time series Physica D 142, 346-382 (2000),
T. Schreiber and A. Schmitz Constrained Randomisation of Time Series for Nonlinearity Tests A. Mees, ed., Nonlinear Dynamics and Statistics, Birkhäuser Boston (2000)
A. Schmitz and T. Schreiber Surrogate data for non-stationary signals K. Lehnertz, C. E. Elger, J. Arnhold, and P. Grassberger, eds., Proceedings ``Chaos in Brain?'', World Scientific, Singapore (2000)
A. Schmitz and T. Schreiber, Testing for nonlinearity in unevenly sampled time series , Phys. Rev. E 59, 4044 (1999)
T. Schreiber and A. Schmitz, Constrained randomisation of time series for hypothesis testing , in Proceedings of NOLTA 1998, Presses Polytechniques et Universitaires Romandes, Lausanne (1998).
T. Schreiber and A. Schmitz, Classification of time series data with nonlinear similarity measures, Phys. Rev. Lett. 79, 1475 (1997)
T. Schreiber and A. Schmitz, Discrimination power of measures for nonlinearity in a time series, Phys. Rev. E 55, 5443 (1997)
T. Schreiber and A. Schmitz, Improved surrogate data for nonlinearity tests, Phys. Rev. Lett. 77, 635 (1996)

Andreas Schmitz und Jochen Arnhold, Analyse von Abhängigkeiten zwischen Zeitreihen, Poster für Seminar Nichtlineare Dynamik in der Physik der Umwelt (1999)

For further interesting publications visit Thomas.

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