विधियों की तुलना करें

	फ्रैक्टल विश्लेषण	नमूना एन्ट्रॉपी
क्षेत्र	जटिल तंत्र	जटिल तंत्र
परिवार	Machine learning	Machine learning
उद्भव वर्ष	1983	2000
प्रवर्तक	Benoit Mandelbrot	Richman & Moorman
प्रकार	Geometric complexity quantification	Nonlinear entropy measure
मौलिक स्रोत	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.
उपनाम	Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz	SampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure
संबंधित	2	2
सारांश	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.