Revisiting algorithms for generating surrogate time series

نویسندگان

  • Christoph Räth
  • M. Gliozzi
  • I. E. Papadakis
  • W. Brinkmann
چکیده

The method of surrogates is one of the key concepts of nonlinear data analysis. Here, we demonstrate that commonly used algorithms for generating surrogates often fail to generate truly linear time series. Rather, they create surrogate realizations with Fourier phase correlations leading to nondetections of nonlinearities. We argue that reliable surrogates can only be generated, if one tests separately for static and dynamic nonlinearities.

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عنوان ژورنال:
  • Physical review letters

دوره 109 14  شماره 

صفحات  -

تاریخ انتشار 2012