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Detecting nonlinearity and phase synchronization with surrogate data

Milan Palus
Institute of Computer Science, Academy of Sciences of the Czech Republic
Pod vodárenskou vezí 2, 182 07 Prague 8, Czech Republic

Dirk Hoyer
Institute for Pathophysiology, Clinical Center of Friedrich-Schiller-University
07740 Jena, Germany


A hypothesis testing approach utilizing the technique of surrogate data is used for detecting nonlinearity and phase synchronization in bivariate time series. Instantaneous phases are obtained by means of discrete Hilbert transform. Information-theoretic functionals -- redundancies are used as the test statistics. Described methods are illustrated in detecting certain nonlinearities and synchronization in cardio-respiratory interactions in the case of a newborn piglet during quiet sleep.

IEEE Engineering in Medicine and Biology Vol. 17 No. 6 (1998) 40-45

Milan Palus 1998