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DY: Fachverband Dynamik und Statistische Physik

DY 28: Data Analysis Methods and Modelling of Geophysical Systems

DY 28.6: Vortrag

Donnerstag, 29. März 2012, 16:15–16:30, MA 144

Signal analysis and classification using ordinal patterns — •Ulrich Parlitz, Sebastian Berg, and Stefan Luther — Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Am Fassberg 17, 37077 Göttingen

Ordinal patterns [1-5] describe the relations within short segments of a given time series. They are easy to compute and robust against noise. For this reason ordinal patterns have been used in a wide range of applications like detection of determinism in noisy time series [4], estimation of transfer entropy in epilepsy [3], or complexity analysis of time series [1,2]. In this contribution we shall present and discuss applications of ordinal pattern statistics for synchronization analysis, forecasting and signal classification. In particular very promising applications to ECG data [5] will be discussed which show that symbolic dynamics based on ordinal patterns provides a powerful tool for coping with data from life sciences.

[1] J.M. Amigo, Permutation Complexity in Dynamical Systems,

Springer Series in Synergetics, Springer-Verlag Berlin Heidelberg

(2010).

[2] C. Bandt and B. Pompe, Phys. Rev. Lett. 88, 174102 (2002).

[3] M. Staniek and K. Lehnertz, Phys. Rev. Lett. 100, 158101 (2008).

[4] J.M. Amigo et al., EPL 79 50001 (2007); EPL 83, 60005 (2008).

[5] U. Parlitz et al., "Classifying cardiac biosignals using ordinal

pattern statistics and symbolic dynamics", to appear in:

Computers in Biology and Medicine, available online 20 April 2011,

doi:10.1016/j.compbiomed.2011.03.017