Create a notch filter for complex input data
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I have a complex sampled signal where I want to filter out the signal at 244140 Hz with an Fs = 390625.
What I tried was:
% See the pic for what the signal looks like
d = fdesign.notch('N,F0,BW,Ap',200,0.625,0.045,1);
Hd = design(d);
y = filter(Hd,myComplexData);
But
- The notch didn't show up where I thought it would
- It is not complex
Now because it is not generating a filter with complex coefficients I understand why the notch is at where it is at.
My questions is: How do I create a complex coefficient filter?
3 Comments
Answers (2)
Uladzimir
on 12 Aug 2015
Edited: Uladzimir
on 12 Aug 2015
Maybe it will help you
F = 244140;
Fs = 390625;
NFFT = length(YourSignal);%or 2^n
YourSpectra = fft(YourSignal,NFFT);
df = Fs/NFFT;% or, if your signal is complex, this must be a known parameter
Ns = round(F/df)+1;
ComplexHarmonic = 2*YourSpectra(Ns);
2 Comments
Uladzimir
on 13 Aug 2015
I just showed an idea with frequency transform. If you have already complex signal, 2x isn't needed, just in a case of fourier transform. You have a signal in a frequency domain. And need a value of one bin on the definite frequency. So, you just need to know the number of this bin.
Ns = round(F/df);
ComplexValue = ComplexSignal(Ns);
Billy Kihei
on 22 Jan 2021
Multiplication in frequency domain is convolution in time domain. (this works for real or complex)
- Take x[t] -> fft -> Y[f]
- zero out the values in Y[f] you want to get rid of -> Ymanuallyfiltered[f]
- Ymanuallyfiltered[f]->ifft->x_filtered[t]
- x_filtered[t]->fft->Yfiltered[f]
Note: This may make your code take much longer to run, but it's a quick and dirty way without designing a filter. It is important that you convert it back to time domain after your manually editing. Then re-fft it to get the natural frequency of the response after filtering. Hope this helps.
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