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.
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.