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perform time-frequency and wavelet analysis of signals and images

wavelet toolbox™ provides apps and functions for the time-frequency analysis of signals and multiscale analysis of images. you can denoise and compress data, and detect anomalies, change-points, and transients. the toolbox enables data-centric artificial intelligence (ai) workflows by providing time-frequency transforms and automated feature extractions, including scattering transforms, continuous wavelet transforms (scalograms), wigner-ville distribution, and empirical mode decomposition. you can extract edges and oriented features from images using wavelet, wavelet packet, and shearlet transforms.

the apps let you interactively perform time-frequency analysis, signal denoising, or image analysis, and generate matlab® scripts to reproduce or automate your work.

you can generate c/c and cuda® code from toolbox functions for embedded deployment.

learn the basics of wavelet toolbox

time-frequency analysis

cwt, constant-q transform, empirical mode decomposition, wavelet coherence, wavelet cross-spectrum

discrete multiresolution analysis

dwt, modwt, dual-tree wavelet transform, shearlets, wavelet packets, multisignal analysis

denoising and compression

wavelet shrinkage, nonparametric regression, block thresholding, multisignal thresholding

ai for signals and images

wavelet-based techniques for machine learning and deep learning, gpu acceleration, hardware deployment, signal labeling

filter banks

orthogonal and biorthogonal wavelet and scaling filters, lifting

code generation and gpu support

generate c/c and cuda code and mex functions, and run functions on a graphics processing unit (gpu)

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