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Wolfram U

Wavelet Applications: Wolfram U Class

via Wolfram U

Overview

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Video class presents wavelet analysis examples, including financial time series, edge detection and denoising of images, thresholding, image & data compression, image fusion.

Course Overview
This video class presents examples from a variety of applications, including financial time series, edge detection and denoising of images, thresholding, image and data compression and image fusion. Familiarity with Fourier transforms and data smoothing methods is recommended for this class.Featured Products & Technologies: Wolfram Language (available in Mathematica and Wolfram|One)
You'll Learn To


Analyze a time series using wavelets for detecting discontinuities, isolating peaks and inspecting nonstationary behavior
Apply wavelet analysis to financial data
Detect edges and discontinuities in images and other two-dimensional data
Reduce noise in images by removing higher-frequency components


Perform wavelet thresholding using various methods
Compress image and data using wavelet packet transforms, wavelet best basis and wavelet thresholding
Combine two images in a variety of ways using wavelet analysis

Syllabus

  • Analyze a time series using wavelets for detecting discontinuities, isolating peaks and inspecting nonstationary behavior
  • Apply wavelet analysis to financial data
  • Detect edges and discontinuities in images and other two-dimensional data
  • Reduce noise in images by removing higher-frequency components
  • Perform wavelet thresholding using various methods
  • Compress image and data using wavelet packet transforms, wavelet best basis and wavelet thresholding
  • Combine two images in a variety of ways using wavelet analysis

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