قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| التماسك الموجي (Wavelet Coherence)× | تحويل المويجات المتقاطع× | |
|---|---|---|
| المجال | السلاسل الزمنية | السلاسل الزمنية |
| العائلة | Process / pipeline | Process / pipeline |
| سنة النشأة≠ | 1999 | 1998 |
| صاحب الطريقة | Christopher Torrence | Christopher Torrence |
| النوع≠ | Multi-scale correlation and phase | Bivariate wavelet interaction |
| المصدر التأسيسي≠ | Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of Climate, 12(8), 2679–2690. DOI ↗ | Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61–78. DOI ↗ |
| الأسماء البديلة≠ | WTC, Wavelet coherency, Continuous wavelet coherence | XWT, Cross-spectrum wavelet |
| ذات صلة | 1 | 1 |
| الملخص≠ | Wavelet coherence (WTC) is a normalized measure of correlation between two time series in the time-frequency domain, eliminating the amplitude-dependence of the raw cross-wavelet transform. Introduced by Torrence and Webster (1999) and formalized by Grinsted, Moore, and Jevrejeva (2004), WTC quantifies how tightly two signals are coupled at each time-frequency point, independent of their individual power levels. It is the wavelet analog of classical spectral coherence, revealing time-localized relationships across all frequencies. | The cross-wavelet transform (XWT) is a bivariate extension of the continuous wavelet transform that measures the joint time-frequency representation of two signals. Introduced by Torrence and Compo (1998) and applied extensively by Grinsted, Moore, and Jevrejeva (2004) to geophysical data, XWT reveals where two signals share common spectral power and the phase relationship between them at each time-frequency point. This is the natural generalization of classical cross-spectral analysis to the time-varying domain. |
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