It might be interesting to interpret the output of the fft() function in Matlab. Consider the following simple examples.
fsMHz = 20; % sampling frequency fcMHz = 1.5625; % signal frequency N = 128; % fft size % generating the time domain signal x1T = exp(j*2*pi*fcMHz*[0:N-1]/fsMHz); x1F = fft(x1T,N); % 128 pt FFT figure; plot([-N/2:N/2-1]*fsMHz/N,fftshift(abs(x1F))) ; % sub-carriers from [-128:127] xlabel('frequency, MHz') ylabel('amplitude') title('frequency response of complex sinusoidal signal');
With anpoint fft() and sampling frequency of , the observable spectrum from is split to sub-carriers.
Additionally, the signal at the output of fft() is from . As the frequencies from get aliased to , the operator fftshift() is used when plotting the spectrum.
In the example above, with a sampling frequency of 20MHz, the spectrum from [-10MHz, +10MHz) is divided into 128 sub-carriers with spaced apart by 20MHz/128 = 156.25kHz. The generated signal x1T of frequency 1.5625MHz corresponds to the information on the 10th sub-carrier, which can also be generated in the frequency domain.
% generating the frequency domain signal with subcarrier indices [-N/2:-1 dc 1:N/2-1] x2F = [zeros(1,N/2) 0 zeros(1,9) 1 zeros(1,N/2-10-1)]; % valid frequency on 10th subcarrier, rest all zeros x2T = N*ifft(fftshift(x2F)); % time domain signal using ifft() % comparing the signals diff = x2T – x1T; err = diff*diff’/length(diff)
Plotting the frequency response of a filter
Consider a filter with the a sinc() shaped impulse response. The Matlab code for plotting the frequency response is as follows:
% impulse response of a sinc() filter hT = sinc([-20:20]/3); % consider sample at 30MHz sampling; hF = fft(hT,1024); % 128 pt FFT figure; plot([-512:511]*30/1024,fftshift(abs(hF))) ; xlabel('frequency, MHz') ylabel('amplitude') title('frequency response of sinc filter');
Hopefully, the post provides some insights on the query raised in the comp.dsp thread.
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