Convert signal from time domain to frequency domain with fft

Hello to everyone

I have signal and time arrays. for example;

signal1 = 1x609

signal1 = [0.0068, 0.0166, ..., 0.5054]

T = 1x609

T = [48.4044, 48.6210, ..., 179.1312]

I wrote a code like this to convert this signal to frequency medium, but I don't know how to determine its frequency. I would be very happy if you could help me with this subject.

X=fftshift(fft(signal1));
fs=10;
df=fs/N; % the frequency increment
f=-fs/2:df:fs/2-df;
figure;
plot(f,abs(X));
    

Answer 1

[Star Strider]

If ‘T’ (that I assume is the time vector) is regularly-sampled (constant sampling intervals), first determine the sampling intervals, then use them to calculate the frequency vector:

L = numel(T);                                   % Length Of Time & Signal Vectors
Ts = mean(diff(T));                             % Sampling Interval
Fs = 1/Ts;                                      % Sampling Frequency
Fn = Fs/2;                                      % Nyquist Frequency
Fv2 = linspace((-Fn, Fn, L);                    % Frequency Vector For Two-Sided Fourier Transform 

The fftshift call leads me to believe that the goal is to plot the two-sided Fourier transform.

If the signal is not regularly-sampled, it must be converted to regular sampling to do any reliable signal processing on it. Use the resample function for that purpose first, then calculate the fft and any other signal processing on the resampled signal.

[Zaref Li]

thank you for your interest. If you don't mind, can you combine it with my code above? I'm a little confused.

[Star Strider]

This is the best I can do in that respect —

X = fftshift(fft(signal1));
L = numel(T);                                   % Length Of Time & Signal Vectors
Ts = mean(diff(T));                             % Sampling Interval
Fs = 1/Ts;                                      % Sampling Frequency
Fn = Fs/2;                                      % Nyquist Frequency
Fv2 = linspace((-Fn, Fn, L);                    % Frequency Vector For Two-Sided Fourier Transform 

figure
plot(Fv2, abs(X))
grid
xlabel('Frequency (units)')
ylabel('Amplitude (units)')

.

[Zaref Li]

Thank you for your help. It was said that normalization to the signal should also be common. I was told that I need to divide by the fft size, L. Where do I write this / L statement?

[Star Strider]

As always, my pleasure!

Normalise it in the fft call —

X = fftshift(fft(signal1)/L);

Note — The ‘L’ calculation and assignment needs to go before the ‘X’ calculation and assignment.