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On Some False Chaos Indicators When Analyzing Sampled Data

  • Petra AugustováEmail author
  • Zdeněk Beran
  • Sergej Čelikovský
Part of the Emergence, Complexity and Computation book series (ECC, volume 14)

Abstract

The main aim of this paper is to demonstrate a possible risk of erroneous conclusions made throughout the process of the sampled data analysis. In particular, it will be shown that the false chaotic behavior of the sampled data may be incorrectly derived from the topological similarity with the already well known chaotic systems like that of Lorenz or from the positivity of the largest Lyapunov exponent. The possible faulty conclusions will be demonstrated using some examples that were recently published in various literature sources.

Keywords

Lyapunov Exponent Chaotic Behavior Lorenz System Large Lyapunov Exponent Maximal Lyapunov Exponent 
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

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Petra Augustová
    • 1
    Email author
  • Zdeněk Beran
    • 1
  • Sergej Čelikovský
    • 1
  1. 1.Institute of Information Theory and Automation, v.v.i.Academy of Sciences of the Czech RepublicPrague 8Czech Republic

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