Different results when compearing DFT from fft to the "real" fourier transformation
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Lillebror Sagmen-Andersson
on 18 May 2022
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1003375/image.png)
I'm trying to compare the DFT computed from matlabs fft, to the "real" fourier transformation for the signal that can derived from the figure above. However I can't seem to get the the signals to match.
I do not have access to syms for this.
It is known that T = 3, and a = 1. EDIT : T_0 = 3, || T =/= 3
I have tried doing it likes this:
x=@(t) exp(-a.*t).*((t>=0)&(t<=3)); % a = 1
T=T_0/N_0; %T_0 & N_0 may be choosen to achive T = 3.
omega=linspace(-pi/T,pi/T,4097);
X = (1-exp(-(a+1i*omega)*T))./(a+1i*omega);
t=(0:T:T*(N_0-1))';
xf=T*x(t);
xf(1)=T*(x(T_0)+1)/2;
X_r=fft(xf);
r=[-N_0/2:N_0/2-1]';
omega_r=r*2*pi/T_0;
then using
subplot(211);
plot(omega,abs(X),'r',omega_r,fftshift(abs(X_r)),'bo');
xlabel('\omega');ylabel('|X(\omega)|')
%and
legend('True FT',strcat('DFT with T_0 = ',num2str(T_0),' , N_0 = ',num2str(N_0)));
subplot(212);
plot(omega,angle(X),'r',omega_r,fftshift(angle(X_r)),'bo');
xlabel('\omega'); ylabel('\angle X(\omega)')
legend('True FT',strcat('DFT with T_0 = ', num2str(T_0),' , N_0 = ',num2str(N_0)));
However as you can see the plots do not agree, and I don't see whats is going wrong.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/1003405/image.jpeg)
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More Answers (3)
Paul
on 20 May 2022
Edited: Paul
on 21 May 2022
Hi Lillebror,
Referring only to the code in the original question, it looks like there is a mix up between the variables used to define the duration of the signal and the sample period to generate the samples of the same, but it's hard to say because the entire code is not posted in the question. I think you're looking for something like this.
Define the signal of interest
T = 3; % T defines the duration of the signal
a = 1;
xfunc = @(t) exp(-a.*t).*((t >= 0) & (t <= T)); % a = 1, T = 3
Pick a sampling period Ts. Though not really necessary, choose Ts such that T/Ts is a nice integer
N = 31;
t = linspace(0,T,N);
Ts = t(2); % Ts is the sampling period
Define the frequency vector for the CTFT of x(t) and then compute the CTFT
omega_c = linspace(-pi/Ts,pi/Ts,4097);
XCTFT = (1 - exp(-(a + 1i*omega_c)*T)) ./ (a + 1i*omega_c);
Samples of x(t)
x = xfunc(t);
Adjust the endpoint to account for the effect of impulse sampling at discontinuities. I think this is similar to your adjustment of xf(1).
x(1) = x(1)/2;
x(end) = x(end)/2;
Compute the DFT
XDFT = fft(x);
Do the fftshift and get the associated frequency vector for N odd
XDFT = fftshift(XDFT);
omega_n = (-(N-1)/2 : (N-1)/2)*2*pi/N/Ts;
Compare, note the scaling by Ts on the DFT
figure
subplot(211);hold on
plot(omega_c,abs(XCTFT));
stem(omega_n,abs(Ts*XDFT));
subplot(212);hold on
plot(omega_c,180/pi*angle(XCTFT));
stem(omega_n,180/pi*angle(T*XDFT));
xlabel('rad/sec')
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Michal
on 18 May 2022
Can you clarify the purpose of this operation (why multiply by T?):
t=(0:T:T*(N_0-1))';
xf=T*x(t)
I'm not following your operations with the time axis, sorry
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