Hi All,
I found mvfft in R and fft2 in Matlab give different result
and can't figure out why. My example is:
In R:
matrix(c(1,4,2,20), nrow=2)
[,1] [,2]
[1,]12
[2,]4 20
mvfft(matrix(c(1,4,2,20), nrow=2))
[,1] [,2]
[1,] 5+0i 22+0i
[2,] -3+0i -18+0i
In Matlab:
Li Li said the following on 5/2/2007 4:06 PM:
Hi All,
I found mvfft in R and fft2 in Matlab give different result
and can't figure out why. My example is:
In R:
matrix(c(1,4,2,20), nrow=2)
[,1] [,2]
[1,]12
[2,]4 20
mvfft(matrix(c(1,4,2,20), nrow=2))
[,1]
Thanks for both replies.
Then I found the ifft2 from Matlab gives different result from fft( ,
inverse=T) from R.
An example:
in R:
temp - matrix(c(1,4,2, 20), nrow=2)
fft(temp)
[,1] [,2]
[1,] 27+0i -17+0i
[2,] -21+0i 15+0i
fft(temp,inverse=T)
[,1] [,2]
[1,] 27+0i -17+0i
Discrete Fourier transforms can be normalized in different ways.
Some apply the whole normalization to the forward transform, some to
the reverse transform, some apply the square root to each, and some
don't normalize at all (in which case the reverse of the forward
transform will need
Li Li said the following on 5/2/2007 7:53 PM:
Thanks for both replies.
Then I found the ifft2 from Matlab gives different result from fft( ,
inverse=T) from R.
An example:
in R:
temp - matrix(c(1,4,2, 20), nrow=2)
fft(temp)
[,1] [,2]
[1,] 27+0i -17+0i
[2,] -21+0i 15+0i
