fft normalization and parseval
7 vues (au cours des 30 derniers jours)
Afficher commentaires plus anciens
h=complex(randi([-1 1],128,1),randi([-1 1],128,1));
h=h/std(h); % no h is normalized to unit pow thus var(h)=1
t=128*ifft(h);
k=var(t);
f=fft(t)/128
g=var(f);
my problem is that k(power in time ) not = g(power in freq) also i have done normalizatoin so that parseval therom applies
any help please
0 commentaires
Réponse acceptée
Matt J
le 25 Mai 2014
Modifié(e) : Matt J
le 25 Mai 2014
also i have done normalizatoin so that parseval therom applies
No, you haven't, I'm afraid. For a length-N fft, the proper normalization is
Y=fft(X)/sqrt(N);
XX=sqrt(N)*ifft(Y);
For example,
>> X=rand(1,10);
>> Y=fft(X)/sqrt(10); XX= sqrt(10)*ifft(Y);
>> norm(X), norm(Y), norm(XX)
ans =
2.3117
ans =
2.3117
ans =
2.3117
2 commentaires
Matt J
le 25 Mai 2014
yasser Commented
@Matt J thanks but please provide a ref for your normalization factor as i saw lots of codes doing as i did without the sqrt issue
Matt J
le 25 Mai 2014
Modifié(e) : Matt J
le 25 Mai 2014
As you can see from the formula in the FFT documentation

the formula for the transform that MATLAB uses is non-orthogonal by a factor of sqrt(N). Normalizing by N and 1/N is what is needed when using FFTs to compute Fourier Series coefficients, see the formulas here
Plus de réponses (2)
George Papazafeiropoulos
le 25 Mai 2014
In the following code:
var1=128;
h=complex(randi([-1 1],var1,1),randi([-1 1],var1,1));
h=h/std(h); % no h is normalized to unit pow thus var(h)=1
t=var1*ifft(h);
k=var(t)
f=fft(t)/var1;
g=var(f)
you have specified var1=128. Try to increase var from 128 to larger values. The two results will eventually converge.
0 commentaires
Voir également
Catégories
En savoir plus sur Fourier Analysis and Filtering dans Help Center et File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!