Continuous Time Fourier Transform of a signal matrix
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Anubhav Rohatgi
el 28 de Jul. de 2012
Respondida: Juhi Maraskole
el 16 de Sept. de 2020
I have a matrix of 100 rows and 2 columns. Column 1 consists of time signal at frequency 50Hz (0.02 0.04 0.06...) column 2 is signal whose fft is to be determined. I would like to have a function that determines the Fourier transform of the signal at the frequency determined by the 1st column of the matrix.
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Wayne King
el 28 de Jul. de 2012
Editada: Wayne King
el 28 de Jul. de 2012
If the first column of your matrix is just the time vector with increments of 0.02 seconds, then just take the Fourier transform of the 2nd column
Let X be your matrix
xdft = fft(X(:,2));
If the signal is real-valued, you only need 1/2 the DFT to examine the amplitude spectrum.
The frequency vector can be formed as follows:
freq = 0:50/100:25;
For example:
t = 0:0.02:(100*0.02)-0.02;
x = cos(2*pi*10*t)+randn(size(t));
X(:,1) = t';
X(:,2) = x';
% Now X is your matrix
xdft = fft(X(:,2));
xdft = xdft(1:length(xdft)/2+1);
freq = 0:50/100:25;
plot(freq,abs(xdft))
xlabel('Hz'); ylabel('Magnitude')
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Wayne King
el 28 de Jul. de 2012
Editada: Wayne King
el 28 de Jul. de 2012
You stated in your original post that your matrix had an even number of elements, 100x2. In fact your matrix is 9079x2. You data also has a mean which is nonzero so that will make the 0 frequency component very large, it's better to remove the mean first.
x = data(:,2);
x = detrend(x,0);
len = length(x)
t = 0:0.02:(len*0.02)-0.02;
xdft = fft(x);
xdft = xdft(1:(length(xdft)+1)/2);
freq = 0:50/len:25;
plot(freq,abs(xdft))
xlabel('Hz'); ylabel('Magnitude')
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