On 07.03.2013, at 16:27, Thomas Young wrote: > Your mean square error procedure is slightly incorrect. You should take the > final signals from both processes, say A[1..n] and B[1..n], subtract them to > get your error signal E[1..n], then the mean square error is the sum of the > squared error over n. > > Sum( E[1..n]^2 ) / n
that's what i'm doing, no? > > This (MSE) is a statistical approach though and isn't necessarily a great way > of measuring perceived acoustical differences. yes, this is what i'm suspecting. > > It depends on the nature of your signal but you may want to check the error > in the frequency domain (weighted to specific frequency band if appropriate) > rather than the time domain. thanks. will have to think a little bit about it. volker -- dupswapdrop -- the music-dsp mailing list and website: subscription info, FAQ, source code archive, list archive, book reviews, dsp links http://music.columbia.edu/cmc/music-dsp http://music.columbia.edu/mailman/listinfo/music-dsp
