This may be an obvious question - but did you try applying a simple Hamming, Blackman-Harris, etc. window to the data? Before trying EMD?
Pretty much every transform (FFT included) has edge effect problems if the signal is not exactly at a periodic boundary, and it sounds like the SVR prediction would be used to create a kind of "custom" window function for very strange data, but the mirroring process is still assuming it is periodic in some way (by basically wrapping the function, the predicting that) I don't know enough about EMD to know whether you are supposed to window or not, but the slides I just glanced through definitely had tapers at the edges. You may also try moving the "black region" forward until it reaches 0 again - this looks like the natural periodic point of your data, and may greatly improve your prediction even though it is kind of cheating... unless it is always possible to find good "periodic points" and use those (maybe by measuring cyclostationarity/autocorrelation?) Also, is this testing data a good representation of your real dataset? It looks EKG-ish to my eyes. This is cool stuff - thanks for sharing. EMD seems worth investigating... Kyle On Thu, Mar 27, 2014 at 8:53 AM, Jaidev Deshpande < [email protected]> wrote: > > > > On Thu, Mar 27, 2014 at 7:16 PM, Nabil Freij <[email protected]>wrote: > >> Hey, >> >> I've been attempting to create an Empirical Mode Decomposition (EMD) code >> and I came across a paper that removed the edge effects by using SVR to >> predict the signal and then mirror that signal. >> >> I've created an IPython Notebook with background and my example code >> trying to reproduce the SVR prediction. I've also linked the paper but it >> might be behind a paywall, so I can provide the PDF >> as needed. >> >> See: >> >> >> http://nbviewer.ipython.org/urls/raw.githubusercontent.com/nabobalis/pyhht/master/Ipython%20Examples/SVM%20Regression%20Fitting.ipynb?create=1 >> >> Thanks, >> Nabil >> >> >> ------------------------------------------------------------------------------ >> >> _______________________________________________ >> Scikit-learn-general mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/scikit-learn-general >> >> > Hi Nabil, > > This is very interesting. Can you also show how the SVR prediction fits > into the EMD process? I mean, can you show how to go through the entire EMD > pipeline while using this method to remove the edge effects? > > Thanks. > > -- > JD > > > ------------------------------------------------------------------------------ > > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > >
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