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| Rekurrenssikvanttianalyysi (RQA)× | Näyte-entropia× | |
|---|---|---|
| Tieteenala | Kompleksiset järjestelmät | Kompleksiset järjestelmät |
| Menetelmäperhe | Machine learning | Machine learning |
| Syntyvuosi≠ | 2007 | 2000 |
| Kehittäjä≠ | Marwan, Romano, Thiel & Kurths | Richman & Moorman |
| Tyyppi≠ | Nonlinear time-series characterization | Nonlinear entropy measure |
| Alkuperäislähde≠ | 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 ↗ | 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. DOI ↗ |
| Rinnakkaisnimet | RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi | SampEn, Sample Entropy (SampEn), Örneklem Entropisi, Nonlinear Complexity Measure |
| Liittyvät | 2 | 2 |
| Tiivistelmä≠ | 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. | 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. |
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