This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English version of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materials including this page, select Japan from the country navigator on the bottom of this page.

Continuous Wavelet Analysis

CWT, scalogram, wavelet coherence, wavelet cross-spectrum, real- and complex-valued wavelets

You can use the continuous wavelet transform (CWT) to analyze how the frequency content of a signal changes over time. For two signals, wavelet coherence reveals common time-varying patterns. For images, continuous wavelet analysis shows how the frequency content of an image varies across the image and helps to reveal patterns in a noisy image. To obtain sharper resolution and extract oscillating modes from a signal, you can use wavelet synchrosqueezing.

Use Wavelet Toolbox™ to obtain the CWT of signals and images. You can use the CWT to obtain the wavelet coherence between two signals. You can also reconstruct time-frequency localized approximations to signals.

Featured Examples

Was this topic helpful?