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Forgot to mention, my environment is python 3.9.15, numba 0.57.0
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I forget to update this repo sometimes but there's been research on this algo out there.. i used it in some other works..
check itd_accelerated.py in a moment, i'll add a file
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https://colab.research.google.com/drive/10yOIApdulVYBLu-jQNoEI5LgnhuD_D2t?usp=sharing
here's a demo. I'm not entirely sure that the behavior is what is intended but it's been a while since i played with ITD.
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Thank you for your help! I started with EMD and then stumbled across ITD, which seems to be a better decomposition method. I do want to say thank you for your great job in this github as it collects so many valuable information in this area. If ITD is a subject your studied a while ago, I am keen to know what's your latest discovery in this direction. :-)
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well, i also developed a method called sifted for decomposition, but it's mostly just iteration + noise decomposition.
there a lot of decomposition methods out there. I have implemented a few.
PVD is another approach. what's important is to understand what you're trying to get out of your data
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