Salīdzināt metodes

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