Analyses of transient chaotic time series

Mukeshwar Dhamala, Ying-Cheng Lai, Eric Kostelich

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

The applicability of the Grassberger-Procaccia (GP) algorithm for estimating the correlation dimension of the chaotic saddle from an ensemble of transient chaotic time series is demonstrated. A numerical procedure is given with an example of the Hènon map to find the rates of separation of neighboring phase-space states constructed from each transient time series in an ensemble to extract Lyapunov exponents. It is also shown that unstable periodic orbits of low period can be detected reliably from an ensemble of transient chaotic time series by using the LK algorithm.

Original languageEnglish (US)
Article number056207
Pages (from-to)056207/1-056207/9
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume64
Issue number5 II
DOIs
StatePublished - Nov 2001

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

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