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Question

I'm trying to apply a bandpass around freq 0 without luck. I'd be happy to receive some help please

x=scan11(1,:)*1e-3/3e8; y=scan11(2,:);
plot(x,y)  % my function

[XX,ff]=trans_fourier(y,mean(diff(x)));
plot(ff,abs(XX))  % gives the Fourier transform

I want to choose the freq around 0. let's suppose -1e13 till 1e13 and than to make ifft and to plot the signal after this filer.

How should I start doing this? the command

YY=bandpass(y,[-1e13 1e13],1/mean(diff(x)))

didn't help here unfortunately.

Since, i can't upload here files, here is also my question on matlab forum with all the files

matlab link

Answer 1

I am not sure what the contents of the trans_fourier function exactly are, but in 'plain matlab functions', you could attempt something along the lines of the following.

Nt = 1024;                     % Number of samples
Fs = 10;                       % Sampling frequency (samples / second)
t = (0:Nt-1)/Fs;               % Time array
x = sin(t/10);                 % Low-frequency signal
x = x + 0.25*randn(1,Nt);      % add some noise

X = fftshift(fft(x));          % FFT of signal with 0 Hz centered
fr = (-Nt/2 : Nt/2-1)/(Nt/Fs); % Frequency axis

% Filter: squared cosine (edit as desired)
fsl = 10;                      % Length of filter slope, in samples
filt = zeros(size(X));
filt(Nt/2+1+(-fsl:fsl)) = cos( linspace(-pi/2,pi/2,2*fsl+1) ).^2;

x_filt = real(ifft(ifftshift( filt.*X ))); % Filtered x

figure();
subplot(2,2,1); plot(t,x);             ax=axis;  title('original signal');
subplot(2,2,4); plot(t,x_filt);        axis(ax); title('Low-pass filtered signal');
subplot(2,2,2); plot(fr,abs(X));       ax=axis;  title('original amplitude spectrum');
subplot(2,2,3); plot(fr,abs(X).*filt); axis(ax); title('Filtered amplitude spectrum');

I am not sure what exactly you meant when you said

let's suppose -1e13 till 1e13

, but keep in mind that extracting a single fourier component (essentially setting all values of the spectrum to zero, except the one you are interested in) acts as a brick-wall filter, and you will get considerable artefacts if you take the inverse transform. Refer to this topic or this page if you're interested.