Communications Physics (Aug 2021)

Ordinal patterns-based methodologies for distinguishing chaos from noise in discrete time series

  • Massimiliano Zanin,
  • Felipe Olivares

DOI
https://doi.org/10.1038/s42005-021-00696-z
Journal volume & issue
Vol. 4, no. 1
pp. 1 – 14

Abstract

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Here, Zanin and Olivares review the permutation patterns-based metrics used to distinguish chaos from stochasticity in discrete time series. They analyse their performance and computational cost, and compare their applicability to real-world time series.