Analyses of transient chaotic time series

Research output: Contribution to journalArticle

39 Citations (Scopus)

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)
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume64
Issue number5 II
StatePublished - Nov 2001

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Chaotic Time Series
Ensemble
Correlation Dimension
saddles
Saddle
Numerical Procedure
Lyapunov Exponent
Periodic Orbits
Phase Space
estimating
Time series
Unstable
exponents
orbits

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Condensed Matter Physics
  • Statistical and Nonlinear Physics
  • Mathematical Physics

Cite this

Analyses of transient chaotic time series. / Dhamala, M.; Lai, Ying-Cheng; Kostelich, Eric.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 64, No. 5 II, 11.2001.

Research output: Contribution to journalArticle

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