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| Рекурентен квантификационен анализ (RQA)× | Фрактален анализ× | |
|---|---|---|
| Област | Сложни системи | Сложни системи |
| Семейство | Machine learning | Machine learning |
| Година на възникване≠ | 2007 | 1983 |
| Създател≠ | Marwan, Romano, Thiel & Kurths | Benoit Mandelbrot |
| Тип≠ | Nonlinear time-series characterization | Geometric complexity quantification |
| Основополагащ източник≠ | 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 |
| Други названия | RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi | Box-Counting Analysis, Fractal Dimension Estimation, Multifractal Analysis, Fraktal Analiz |
| Свързани | 2 | 2 |
| Резюме≠ | 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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