Wavelet Toolbox™ provides functions and apps for analyzing and synthesizing signals, images, and data that exhibit regular behavior punctuated with abrupt changes. The toolbox includes algorithms for the continuous wavelet transform (CWT), scalograms, and wavelet coherence. It also provides algorithms and visualizations for discrete wavelet analysis, including decimated, nondecimated, dual-tree, and wavelet packet transforms. In addition, you can extend the toolbox algorithms with custom wavelets.
The toolbox lets you analyze how the frequency content of signals changes over time and reveals time-varying patterns common in multiple signals. You can perform multiresolution analysis to extract fine-scale or large-scale features, identify discontinuities, and detect change points or events that are not visible in the raw data. You can also use Wavelet Toolbox to efficiently compress data while maintaining perceptual quality and to denoise signals and images while retaining features that are often smoothed out by other techniques.
Discover more about Wavelet Toolbox by exploring these resources.
Explore documentation for Wavelet Toolbox functions and features, including release notes and examples.
Browse the list of available Wavelet Toolbox functions.
View system requirements for the latest release of Wavelet Toolbox.
View articles that demonstrate technical advantages of using Wavelet Toolbox.
Wavelet Toolbox requires MATLAB.
Use Wavelet Toolbox to solve scientific and engineering challenges: