Wavelet Toolbox

Key Features

  • Standard wavelet families, including Daubechies wavelet filters, complex Morlet and Gaussian, real reverse biorthogonal, and discrete Meyer
  • Wavelet and signal processing utilities, including a function to convert scale to frequency
  • Methods for adding wavelet families
  • Lifting methods for constructing wavelets
  • Customizable presentation and visualization of data
  • Wavelet Design and Analysis app for continuous and discrete wavelet analysis
  • Wavelet packets, implemented as MATLAB objects
  • One-dimensional multisignal analysis, compression, and denoising
  • Multiscale principal component analysis
  • Multivariate denoising

Wavelet Toolbox authors are Michel Misiti, École Centrale de Lyon; Georges Oppenheim, Université de Marne-La-Vallée; Jean-Michel Poggi, Université René Descartes, Paris 5 Université; and Yves Misiti, Université Paris-Sud.

Next: Applying Wavelet Methods

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