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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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;
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')
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')
I have tried to solve the problem but the plot I get is not what I want. I have breathing data that is very periodic. I have attached the data link to this
I want to get frequency peaks at around 3Hz.
Please help me.
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