Why the amplitude of fft computing is a little bit different from a known value?
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    André Luiz Regis Monteiro
 on 21 Jul 2014
  
    
    
    
    
    Commented: André Luiz Regis Monteiro
 on 4 Aug 2014
            I was trying test this:
n=5000;
ts=5;
t=[0:ts/n:ts];
x1=sin(2*pi*20*t);
x2=2*sin(2*pi*60*t);
x3=20*sin(2*pi*200*t);
x4=15*sin(2*pi*350*t);
x=x1+x2+x3+x4;
N=length(x);
k=[0:N-1];
T=N/Fs;
freq=k/T;
cutoff=ceil(N/2);
X=fftn(x)/(N/2);
X=abs(X);
stem(freq(1:cutoff),X(1:cutoff))
The magnitudes got different results to 1 (x1); 2 (x2); 20 (x3) and 15 (x4). And more...if "n" has more or less points for computing the fft, the frequencies (20, 60, 200, 350) also change. Why? Can someone help me? Thanks a lot.
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Accepted Answer
  Wayne King
    
      
 on 21 Jul 2014
        
      Edited: Wayne King
    
      
 on 21 Jul 2014
  
      You have to realize that the frequency spacing between DFT elements depends on the length of the DFT and the sampling frequency. If your frequencies do not fall directly on a DFT bin (the spacing is Fs/N where Fs is the sampling frequency and N the length of the DFT) then the energy in a particular component will be mapped to a slightly different frequency.
Here is your example the way you think it should look:
n=5000; ts=5; t=[0:ts/n:ts-ts/n];
x1=sin(2*pi*20*t); x2=2*sin(2*pi*60*t); x3=20*sin(2*pi*200*t);    
x4=15*sin(2*pi*350*t); x=x1+x2+x3+x4;
xdft = fft(x);
xdft = xdft(1:length(x)/2+1);
xdft(2:end-1) = 2*xdft(2:end-1);
xdft = xdft./length(x);
df = 1000/length(x);
freq = 0:df:500;
plot(freq,abs(xdft));
xlabel('Hz'); ylabel('Magnitude');
grid on;
You may want to review this:
3 Comments
  Wayne King
    
      
 on 22 Jul 2014
				Andre, the frequency spacing in the DFT is Fs/N where Fs is the sampling frequency and N is the number of DFT points.
If you change N = 512, then the frequency spacing is 1000/512. As a result the frequencies in your signal may not correspond to a DFT bin.
For example, your frequency spacing would be 1000/512=1.9531 and 350 is not divisible by 1.9531. Accordingly, the energy in that signal may not get perfectly mapped to one DFT bin and the amplitude estimation may be off. Did you read the example in the link I provided? That is explained.
To get the amplitude correct on a one-sided DFT magnitude plot, yo have to multiply all the frequencies that occur twice in the DFT by 2.
Yes,
df = (n/ts)/length(x);
because (n/ts) is equal to the sampling frequency.
Thank you for accepting my answer if I have helped you.
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