ANALYSIS OF CHAOTIC DATA WITH MATHEMATICA
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 cor...
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| Veröffentlicht in: | Chaos and complexity letters Jg. 9; H. 1; S. 53 |
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| 1. Verfasser: | |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Hauppauge
Nova Science Publishers, Inc
01.01.2015
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| Schlagworte: | |
| ISSN: | 1556-3995, 2374-054X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | 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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| Bibliographie: | SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1556-3995 2374-054X |