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(→Tutorials: Added False Nearest Neighbors) |
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Please download it as the tutorial will reference it. | Please download it as the tutorial will reference it. | ||
=== False Nearest Neighbors === | === False Nearest Neighbors === | ||
This function uses a method to determine the minimum sufficient embedding dimension. | This function uses a method to determine the minimum sufficient embedding dimension. As a demonstration we will create a plot that contains an Ikeda Map, a Henon Map and a Henon Map corrupted by 10% of Gaussian noise. | ||
{{Code|Analyzing false nearest neighbors|<syntaxhighlight lang="octave" style="font-size:13px"> | |||
# Create maps | |||
ikd = ikeda (10000); | |||
hen = henon (10000); | |||
hen_noisy = hen + std (hen) * 0.02 .* (-6 + sum (rand ([size(hen), 12]), 3)); | |||
# Create and plot false nearest neighbors | |||
[dim_ikd, frac_ikd] = false_nearest (ikd(:,1)); | |||
[dim_hen, frac_hen] = false_nearest (hen(:,1)); | |||
[dim_hen_noisy, frac_hen_noisy] = false_nearest (hen_noisy(:,1)); | |||
plot (dim_ikd, frac_ikd, '-b*', 'markersize', 15,... | |||
dim_hen, frac_hen, '-r+', 'markersize', 15,... | |||
dim_hen_noisy, frac_hen_noisy, '-gx', 'markersize', 15); | |||
</syntaxhighlight>}} | |||
From this chart we can conclude the sufficient embedding dimension for each system. For a Henon Map {{Codeline|m = 2}} is sufficient, but for an Ikeda map it is better to use {{Codeline|m = 3}}. | |||
=== Nonlinear Prediction === | === Nonlinear Prediction === | ||
In this section we will demonstrate some functions from the 'Nonlinear Prediction' chapter of the TISEAN documentation (located [http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/docs/chaospaper/node16.html#SECTION00050000000000000000 here]). For now this section will only demonstrate functions that are connected to the [http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/docs/chaospaper/node18.html#SECTION00052000000000000000 Simple Nonlinear Prediction] section. <br/> | In this section we will demonstrate some functions from the 'Nonlinear Prediction' chapter of the TISEAN documentation (located [http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/docs/chaospaper/node16.html#SECTION00050000000000000000 here]). For now this section will only demonstrate functions that are connected to the [http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/docs/chaospaper/node18.html#SECTION00052000000000000000 Simple Nonlinear Prediction] section. <br/> |
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