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| Самоорганизираща се критичност× | Рекурентен квантификационен анализ (RQA)× | |
|---|---|---|
| Област | Сложни системи | Сложни системи |
| Семейство≠ | Regression model | Machine learning |
| Година на възникване≠ | 1987 | 2007 |
| Създател≠ | Per Bak, Chao Tang & Kurt Wiesenfeld | Marwan, Romano, Thiel & Kurths |
| Тип≠ | Dynamical systems model | Nonlinear time-series characterization |
| Основополагащ източник≠ | Bak, P., Tang, C., & Wiesenfeld, K. (1987). Self-organized criticality: An explanation of 1/f noise. Physical Review Letters, 59(4), 381–384. DOI ↗ | 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 ↗ |
| Други названия | SOC, Sandpile Model, Critical Self-Organization, Kendiliğinden Örgütlenen Kritiklik | RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi |
| Свързани≠ | 3 | 2 |
| Резюме≠ | Self-Organized Criticality (SOC) is a dynamical systems framework introduced by Per Bak, Chao Tang, and Kurt Wiesenfeld in 1987 to explain how large, dissipative systems spontaneously evolve toward a critical state without external fine-tuning. At the critical state, the system produces scale-invariant fluctuations — avalanches whose size and duration follow power-law distributions — and generates 1/f (pink) noise in its power spectrum. | 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. |
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