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 scaling).
The latter apparently the case with R, according to your values. Note that the R and the MatLab answers agree to within a scale factor for each row. At 10:53 PM 5/2/2007, Li-Li wrote: >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 >[2,] -21+0i 15+0i > >In Matlab: > > A = [1,2;4,20]; > > fft2(A) >Ans = > 27 -17 > -21 15 > >ifft2(A) >Ans= > 6.7500 -4.2500 > -5.2500 3.7500 > >I also tried mvfft with inverse but can't get same result with "ifft2". Does >any function work? ================================================================ Robert A. LaBudde, PhD, PAS, Dpl. ACAFS e-mail: [EMAIL PROTECTED] Least Cost Formulations, Ltd. URL: http://lcfltd.com/ 824 Timberlake Drive Tel: 757-467-0954 Virginia Beach, VA 23464-3239 Fax: 757-467-2947 "Vere scire est per causas scire" ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
