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Fraktální analýza×Sample Entropy×
OborKomplexní systémyKomplexní systémy
RodinaMachine learningMachine learning
Rok vzniku19832000
TvůrceBenoit MandelbrotRichman & Moorman
TypGeometric complexity quantificationNonlinear entropy measure
Původní zdrojMandelbrot, B. B. (1983). The Fractal Geometry of Nature. W. H. Freeman. ISBN: 978-0-7167-1186-5Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology, 278(6), H2039–H2049. DOI ↗
Další názvyBox-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal AnalizSampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure
Příbuzné22
ShrnutíFractal Analysis quantifies the self-similar, scale-invariant complexity of geometric objects and time series through the fractal dimension D and the Hurst exponent H. Introduced systematically by Benoit Mandelbrot in his 1983 landmark work, the framework extends classical Euclidean geometry to irregular shapes found in nature, finance, physiology, and materials science. It provides a single dimensionless index that captures how completely a pattern fills space across multiple scales.Sample Entropy (SampEn) is a nonlinear measure of the complexity and regularity of a time series. Introduced by Richman and Moorman in 2000 as an improvement over Approximate Entropy (ApEn), it quantifies the likelihood that similar patterns of a given length in the series remain similar when extended by one additional data point. A higher SampEn value indicates greater irregularity and complexity, while a lower value indicates more regularity or self-similarity.
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ScholarGatePorovnat metody: Fractal Analysis · Sample Entropy. Získáno 2026-06-15 z https://scholargate.app/cs/compare