An Investigation of the Ability of Nonlinear Methods to Infer Dynamics from Observables

作者: A. A. Tsonis , G. N. Triantafyllou , J. B. Elsner , J. J. Holdzkom , A. D. Kirwan

DOI: 10.1175/1520-0477(1994)075<1623:AIOTAO>2.0.CO;2

关键词: Statistical physicsMathematicsObservableDynamics (music)Dynamical systemDimension (vector space)Lyapunov exponentNonlinear systemVariety (cybernetics)CalculusCharacter (mathematics)Atmospheric Science

摘要: Abstract In this study analysis of data whose character was kept secret performed by employing a variety nonlinear approaches. The idea to test the ability approaches stemming from theory dynamical systems infer true properties hidden in data. employed include dimension estimation, prodiction, Lyapunov exponent and false nearest neighbors. It is concluded that even though methods have problems occasionally may be inconclusive, when correctly applied they are effective delineating dynamics underlying

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