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循环量化分析 (RQA)×分形分析×
领域复杂系统复杂系统
方法族Machine learningMachine learning
起源年份20071983
提出者Marwan, Romano, Thiel & KurthsBenoit Mandelbrot
类型Nonlinear time-series characterizationGeometric complexity quantification
开创性文献Marwan, N., Romano, M. C., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5–6), 237–329. DOI ↗Mandelbrot, B. B. (1983). The Fractal Geometry of Nature. W. H. Freeman. ISBN: 978-0-7167-1186-5
别名RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon AnaliziBox-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz
相关22
摘要Recurrence Quantification Analysis (RQA) is a nonlinear method for characterizing the dynamics of a time series by quantifying the small-scale structure of its recurrence plot. Introduced in its modern, comprehensive form by Marwan, Romano, Thiel, and Kurths in 2007, RQA extracts scalar measures — such as recurrence rate, determinism, laminarity, and Shannon entropy — that capture periodicity, chaos, stationarity, and transitions in complex dynamical systems.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.
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ScholarGate方法对比: Recurrence Quantification Analysis · Fractal Analysis. 于 2026-06-15 检索自 https://scholargate.app/zh/compare