Symbolic Dynamics from Chaotic Time Series

  • A. Destexhe
  • G. Nicolis
  • C. Nicolis
Part of the NATO ASI Series book series (NSSB, volume 208)

Abstract

Following the ideas of Ruelle and others [1,2], an embedding phase space can be reconstructed from experimental systems on the basis of time series data. The introduction of numerical methods for calculating dimensions, entropies, Lyapunov exponents and other related properties, has permitted extensive investigations of chaotic experimental systems these last years. However, severe restrictions about the applicability of these methods were noticed, especially for high dimensional systems [3–6].

Keywords

Markov Process Lyapunov Exponent Chaotic Dynamic Symbolic Dynamic Chaotic Time Series 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • A. Destexhe
    • 1
  • G. Nicolis
    • 1
  • C. Nicolis
    • 2
  1. 1.Service de Chimie PhysiqueUniversité Libre de BruxellesBruxellesBelgium
  2. 2.Institut d’Aeronomie Spatiale de Belgique1180 BruxellesBelgium

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