Salīdzināt metodes

	Šķērs viļņu transformācija	Viļņu koherence
Nozare	Laikrindas	Laikrindas
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1998	1999
Autors	Christopher Torrence	Christopher Torrence
Tips	Bivariate wavelet interaction	Multi-scale correlation and phase
Pirmavots	Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79(1), 61–78.	Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of Climate, 12(8), 2679–2690.
Citi nosaukumi	XWT, Cross-spectrum wavelet	WTC, Wavelet coherency, Continuous wavelet coherence
Saistītās	1	1
Kopsavilkums	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.	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.