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arXiv · 1511.00529

Measuring the Complexity of Continuous Distributions

Guillermo Santamaría-Bonfil·Nelson Fernández·Carlos Gershenson
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Abstract

We extend previously proposed measures of complexity, emergence, and self-organization to continuous distributions using differential entropy. This allows us to calculate the complexity of phenomena for which distributions are known. We find that a broad range of common parameters found in Gaussian and scale-free distributions present high complexity values. We also explore the relationship between our measure of complexity and information adaptation.

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Guillermo Santamaría-Bonfil, Nelson Fernández, Carlos Gershenson. 2015-11-02. Measuring the Complexity of Continuous Distributions. https://doi.org/10.3390/e18030072

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