A1 Journal article – refereed
Analysis of Chaotic Data with Mathematica




List of Authors: Heikki Ruskeepää
Publisher: Nova Science Publishers, Inc.
Place: Hauppauge NY 11788-3619
Publication year: 2015
Volume number: 9
Issue number: 1
eISSN: 1556-3995

Abstract


We describe Mathematica software for analysis of chaotic data. The software, publicly available from Wolfram Library Archive, contains programs for estimating the delay time (with the method of average mutual information), the embedding dimension (with the method of false nearest neighbors), the correlation dimension (with the method of correlation exponent), and the maximal Lyapunov exponent (with the method of local divergence rates) and programs for nonlinear prediction (with the method of analogues). The use of Mathematica has the advantage that we can build instructive dynamic interfaces to help the researcher in doing some decisions (like defining a scaling region) that are difficult to do automatically. Automatic parallel computation is applied when possible. The software has been applied to data derived from the Hénon, logistic, and Lorenz models as well as to real NMR laser data. In this article, we only show some computations for data derived from the Hénon model.




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Last updated on 2019-29-01 at 12:43