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

AI Thread Summary
The discussion focuses on implementing the Discrete Haar Wavelet Transform (DHWT) for audio signal compression. The original poster seeks resources and a step-by-step algorithm for deconstructing and reconstructing signals using DHWT, as their textbook lacks practical examples. They mention the importance of understanding the orthogonal vector spaces associated with scaling functions and mother wavelets. A suggestion is made to search online for additional resources, indicating that various levels of information are available. The conversation highlights the need for practical guidance in applying theoretical concepts to real-world problems.
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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