How thresholding is done after the decomposition of a signal using discrete wavelet transform?

I have a signal which is the combination of two signals, one of which is relevant to me. I have decomposed the signal into diffeternt details and approximation using discrete wavelet transform. In these two of the details have the part of the signal which is relevant. So I need to do hard thresholding on the part which I dont want. How can I do this? Is there any in-build function for the same?

Answer 1

[Nadia Shaik]

Hi Bipin,

I understand that you want to perform thresholding after the decomposition of a signal using Discrete Wavelet Transform.

You can acheive the required workflow by using 'wdenoise' function.

A wavelet and a level N have to be selected and then the wavelet decomposition of the input signal at level N is computed. For each level from 1 to N, select a threshold and then thresholding is applied to the detail coefficients.

I hope this resolves your query.