# How to extract mean frequency from continuous wavelet transform (CWT)

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Brent on 22 Mar 2017
Commented: Brent on 27 Nov 2017
Hello,
I have used the cwt function in Matlab 2017a to create a scalogram of an electromyography (EMG) signal. My goal is to compare the time varying mean frequencies of different EMG signals. The issue is that I'm not sure how to use the complex double output (wt) to calculate a usable mean frequency 1D waveform.

Santhana Raj on 22 Mar 2017
Hi,
If your question is to how to get useful information from the complex matrix of 'wt', then use the command 'abs' to get the absolute magnitude of the complex variable.
If your question is to how to extract mean data from a vector, then compute the average of the signal. You can do the same for different scales in your wt or overall average value across all scales.
Hope this helps.
Raj
Brent on 27 Nov 2017
Hi Jungyeon. Below is the code I used to calculate IMNF. It's based on the paper above and uses the [wt, f, coi] outputs from the cwt function. you'll likely need to filter the IMNF as the outcome is quite noisy.
wta=abs(wt);
s_max=length(f);
s=1:s_max;
w0 = f(1);
for i=1:size(wta,2)
w=w0./(s(2:end));
IMNFi(i)=trapz(w',w'.*wta(2:end,i))./trapz(w',wta(2:end,i));
end