Σύγκριση μεθόδων

	Εντροπία Δείγματος	Φρακταλική Ανάλυση
Πεδίο	Πολύπλοκα Συστήματα	Πολύπλοκα Συστήματα
Οικογένεια	Machine learning	Machine learning
Έτος προέλευσης	2000	1983
Δημιουργός	Richman & Moorman	Benoit Mandelbrot
Τύπος	Nonlinear entropy measure	Geometric complexity quantification
Θεμελιώδης πηγή	Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology, 278(6), H2039–H2049.	Mandelbrot, B. B. (1983). The Fractal Geometry of Nature. W. H. Freeman. ISBN: 978-0-7167-1186-5
Εναλλακτικές ονομασίες	SampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure	Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz
Συναφείς	2	2
Σύνοψη	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.	Fractal 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.