Quote:
Originally Posted by noah katz 
Chris,
"I'm not sure why you think the corrected curves look worse for LCR. Think for a moment what these curves represent: the spatially combined (we call it clustered) measurements in the listening area. So these are weighted by how common the problems are in different frequency regions across the 7 positions that Ray measured.
.....Perhaps you are referring to the peak at 60-80 Hz."
The link isn't working now, but I believe it was that range.
IIRC, the before/after of two of the fronts would be hard to tell apart if you couldn't see both at once, and one actually had a slightly higher peak after.
The sub OTOH was very flat in the same freq range.
I don't understand how to relate that to what you said re weighting.
Thanks

Chris,
"I'm not sure why you think the corrected curves look worse for LCR. Think for a moment what these curves represent: the spatially combined (we call it clustered) measurements in the listening area. So these are weighted by how common the problems are in different frequency regions across the 7 positions that Ray measured.
.....Perhaps you are referring to the peak at 60-80 Hz."
The link isn't working now, but I believe it was that range.
IIRC, the before/after of two of the fronts would be hard to tell apart if you couldn't see both at once, and one actually had a slightly higher peak after.
The sub OTOH was very flat in the same freq range.
I don't understand how to relate that to what you said re weighting.
Thanks
Noah,
I guess beauty is in the eye of the beholder

There was a big peak centered at 70 Hz and extended out from 60-80 Hz. That peak was reduced in width after the correction. It was not reduced in height.
However, the range between 150 Hz and 250 Hz or so had a big dip in the before plot. In the after plot you can see it coming up to the 0 dB line with some remaining ripple.
The weighting I am referring to has to do with how these plots are generated. They are not a single mic measurement before and after. Rather, they are a combination of multiple measurements. The easy thing to do would be to just average the measurements and show the average plot. But that would be wrong, because it assumes that each measurement contributes equally. MultEQ uses information from each measurement to decide what problems to attack first and then combines the measurements using a method called clustering that is not based on simple averaging. To make things more exciting, all this is done in the time domain and not the frequency domain that you see plotted.
Chris










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