Multifractal surrogate-data generation algorithm that preserves pointwise Hölder regularity structure, with initial applications to turbulence.

  title={Multifractal surrogate-data generation algorithm that preserves pointwise H{\"o}lder regularity structure, with initial applications to turbulence.},
  author={Christopher James Keylock},
  journal={Physical review. E},
  volume={95 3-1},
  • C. Keylock
  • Published 3 January 2017
  • Computer Science
  • Physical review. E
An algorithm is described that can generate random variants of a time series while preserving the probability distribution of original values and the pointwise Hölder regularity. Thus, it preserves the multifractal properties of the data. Our algorithm is similar in principle to well-known algorithms based on the preservation of the Fourier amplitude spectrum and original values of a time series. However, it is underpinned by a dual-tree complex wavelet transform rather than a Fourier transform… 
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