On Fri, 15 Jul 2005, Jacob Last wrote:
Thanks, I would love to see the abstractions, as I was sort of shooting in the dark for a while implementing even the relatively simple spectral centroid. I originally thought I should be able to do the computation all in the signal domain from the [rfft~] object's outputs....is that possible? What I ended up doing is writing each analysis frame into an array, then using [bang~] to trigger the calculation for each frame, reading through the array.
you can compute the centroid of signal chunks using a [phasor~] tuned to ramp up exactly synched with each block, one or two [*~] and then summing or averaging all values in each chunk ([lop~] could do it but there are better ways that I can't think of now).
you can compute higher-order moments using powers. e.g. multiplying a signal with itself for squaring, or [expr~ pow($v1,3)] for cubing, etc. And you insert that right after the [phasor~].
the mean (the centroid) is the 1st-order moment.
the variance is the 2nd-order moment minus the square of the mean, or the other way around...
there are formulæ for skewness and kurtosis that are quite simple combinations of moments.
Entropy is not obtainable using moments, but has a similar formula. You have to do [expr~ $v1*log($v1)] after the [phasor~], or something.
,-o--------o--------o--------o-. ,---. irc.freenode.net #dataflow |
| The Diagram is the Program tm| | ,-o-------------o--------------o-.
-o------------o-------------o-' | | Mathieu Bouchard (Montréal QC) | | téléphone:+1.514.383.3801---' `-o-- http://artengine.ca/matju -'