How to reconstruct a signal using the Discrete Haar Wavelet transform?

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SUMMARY

The discussion centers on implementing the Discrete Haar Wavelet Transform (DHWT) for audio signal compression. The user seeks resources and a step-by-step algorithm for both deconstruction and reconstruction of the signal, as their current textbook focuses on theoretical properties rather than practical applications. Key concepts mentioned include vector spaces V and W, which are orthogonal, and the importance of selecting a resolution j as the initial step in the DHWT process.

PREREQUISITES
  • Understanding of wavelet theory and properties
  • Familiarity with audio signal processing
  • Knowledge of vector spaces and orthogonality
  • Basic programming skills for implementation
NEXT STEPS
  • Research the mathematical foundations of the Discrete Haar Wavelet Transform
  • Explore practical examples of audio signal compression using DHWT
  • Learn about the implementation of wavelet transforms in Python using libraries like PyWavelets
  • Study algorithms for signal reconstruction post-wavelet transformation
USEFUL FOR

This discussion is beneficial for students in signal processing, audio engineers, and developers interested in implementing wavelet transforms for audio compression projects.

XcKyle93
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Homework Statement



Hi, for a project for school, I need to implement the Discrete Haar Wavelet Transform to compress an audio signal. This would be fine and dandy, but I do not really understand how to use the the DHWT. Could anyone direct me towards some resources that would be very helpful in my understanding? If someone could provide a step-by-step algorithm that goes through the deconstruction and reconstruction of the signal, that would be nice. The textbook that I'm using is a math textbook, so it is more interested in proving properties of the filters & wavelets instead giving examples and exercises. This is great, until I actually need to apply it towards something.

Homework Equations


I know that there are vector spaces V and W that are orthogonal to each other; V is associated with the scaling function ∅, W is associated with the mother wavelet ψ. I think the first step in the DHWT is to pick a resolution j, but beyond that I don't understand.

The Attempt at a Solution

 
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Sorry, I had seen that resource and it's much different from what we've done in class.
 

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