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| Synchrosqueezing-muunnos× | Aalto-koherenssi× | |
|---|---|---|
| Tieteenala | Aikasarjat | Aikasarjat |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 2011 | 1999 |
| Kehittäjä≠ | Ingrid Daubechies | Christopher Torrence |
| Tyyppi≠ | Time-frequency decomposition | Multi-scale correlation and phase |
| Alkuperäislähde≠ | Daubechies, I., Lu, J., & Wu, H. T. (2011). Synchrosqueezed wavelet transforms: An empirical tool for time-frequency analysis. Applied and Computational Harmonic Analysis, 30(2), 243–261. link ↗ | Torrence, C., & Webster, P. J. (1999). Interdecadal changes in the ENSO–monsoon system. Journal of Climate, 12(8), 2679–2690. DOI ↗ |
| Rinnakkaisnimet≠ | SST, Synchrosqueezing | WTC, Wavelet coherency, Continuous wavelet coherence |
| Liittyvät≠ | 3 | 1 |
| Tiivistelmä≠ | The synchrosqueezing transform is a time-frequency reassignment technique that sharpens the output of the continuous wavelet transform by concentrating energy along instantaneous frequency ridges. Introduced by Ingrid Daubechies and colleagues in 2011, it addresses the fundamental limitation of the standard wavelet transform: poor frequency localization. This method is particularly valuable for analyzing signals with time-varying frequency content. | 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. |
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