Comparar métodos

	Análisis Fractal	Entropía de Muestra
Campo	Sistemas complejos	Sistemas complejos
Familia	Machine learning	Machine learning
Año de origen	1983	2000
Autor original	Benoit Mandelbrot	Richman & Moorman
Tipo	Geometric complexity quantification	Nonlinear entropy measure
Fuente seminal	Mandelbrot, B. B. (1983). The Fractal Geometry of Nature. W. H. Freeman. ISBN: 978-0-7167-1186-5	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.
Alias	Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz	SampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure
Relacionados	2	2
Resumen	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.	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.