Justin Yang

I am using the last outlet of fiddle~ to get out freq/amp pairs of 

individual sinusoidal components in this case of saxophone 

multiphonics. I would like to get an 'average frequency and amplitude' 

for each component over an adjustable period of time say 15 seconds or 

2 minutes. However, my rudimentary math skills are leaving me quite 

baffled. I know it's not as simple as sticking a mean object on each 

component as high-frequency jumps skew the results and I am looking for 

some waiting of each frequency reported based on its amplitude. 

Basically, if I were to play a single multiphonic for 20 seconds, I 

would like to know what were the, say 7, strongest frequency areas and 

their relative amplitudes. Like an averaged sonogram but in numbers.

Hi,
I am using the last outlet of fiddle~ to get out freq/amp pairs of 
individual sinusoidal components in this case of saxophone 
multiphonics.  I would like to get an 'average frequency and amplitude' 
for each component over an adjustable period of time say 15 seconds or 
2 minutes.  However, my rudimentary math skills are leaving me quite 
baffled.  I know it's not as simple as sticking a mean object on each 
component as high-frequency jumps skew the results and I am looking for 
some waiting of each frequency reported based on its amplitude.   
Basically, if I were to play a single multiphonic for 20 seconds, I 
would like to know what were the, say 7, strongest frequency areas and 
their relative amplitudes.  Like an averaged sonogram but in numbers.

statistical-math-question

I'm not quite sure this answers your problem but one statistical formula 

you might find useful is the running average. Now, I'm not sure exactly 

what you mean by high frequency jumps skewing results and weighting 

based on amplitude so the formula below doesn't address that.

Running average = x * alpha + ((1 - alpha) * previous running average)

As you can see, it's a form of simple feedback algorithm where you plug 

the result of the equation back in. Alpha is a value between 0 and 1. 

Lower values mean longer averaging times. If alpha = 1, no averaging is 

done. This is also useful for smoothing data -- i.e. getting rid of 

I'm not quite sure this answers your problem but one statistical formula 
you might find useful is the running average. Now, I'm not sure exactly 
what you mean by high frequency jumps skewing results and weighting 
based on amplitude so the formula below doesn't address that.

As you can see, it's a form of simple feedback  algorithm where you plug 
the result of the equation back in. Alpha is a value between 0 and 1. 
Lower values mean longer averaging times. If alpha = 1, no averaging is 
done. This is also useful for smoothing data -- i.e. getting rid of 
spikes. See patch below.

Btw, the slide object in MaxMSP 4.5 does this with user settable 

constants for positive and negative deltas (rise and fall).

Btw, the slide object in MaxMSP 4.5 does this with user settable  
constants for positive and negative deltas (rise and fall).

i usualy make fiddle~s output a signal first.

to flatten the intonation line you can now use

lowpassfilters, or slide~, or rampsmooth~.

to control what happens just connect a cycle~ 

i usualy make fiddle~s output a signal first.
to flatten the intonation line you can now use
lowpassfilters, or slide~, or rampsmooth~.
to control what happens just connect a cycle~ 
and listen to it.


On 17-Mar-2006, at 2:06, Jean-Marc Pelletier wrote:

> Running average = x * alpha + ((1 - alpha) * previous running average)

lp.stacey does this automatically. Give her an initialization 

argument specifying how wide your window is (10 data points, 20 data 

points, whatever) and she'll do the math. Follow the URI below to the 

Litter Starter Pack for more information.

I'd give you an example but I don't have fiddle~ installed on this 

Peter Castine | +--> Litter Power & Litter Bundle for Jitter

|....................................................

p@castine.de | iCE: Sequencing, Recording, and Interface Building

4-15@kagi.com |....................................................

On 17-Mar-2006, at 2:06, Jean-Marc Pelletier wrote:
> Running average = x * alpha + ((1 - alpha) * previous running average)

lp.stacey does this automatically. Give her an initialization  
argument specifying how wide your window is (10 data points, 20 data  
points, whatever) and she'll do the math. Follow the URI below to the  
Litter Starter Pack for more information.

I'd give you an example but I don't have fiddle~ installed on this  
machine  yet.

--------------    http://www.bek.no/~pcastine/Litter/    -------------
Peter Castine    |        +--> Litter Power & Litter Bundle for Jitter
                  |....................................................
p@castine.de     | iCE:  Sequencing, Recording, and Interface Building
pcastine@gmx.net |       for Max/MSP
pcastine@bek.no  | http://www.dspaudio.com/             Extremely cool
4-15@kagi.com    |....................................................
                  | home|chez nous|wir|i nostri  http://www.castine.de/

Statistical Math Question