[music-dsp] RMS / time coeff. / gain smoothing (was Please check ...)

[Citizen Chunk]

Furi:

by coincidence, i did a search for "RMS detection TAV" to learn more  
about how the averaging coefficient is formulated, and i found this  
link:  
http://www.ktl.elf.stuba.sk/projects/audio/drc/realization/ 
realization.htm

it seems that someone implemented this in his design. of further note  
is his peak detection difference equation:

  xpeak(n) = (1 – AT – RT) . xpeak(n-1) + AT.|x(n)|

i found it curious that the author incorporated both the attack/release  
coefficients into 1 equation. i am using an if/else structure for  
attack/release.

input = |x|
if ( input > env )
	env = input + AT * ( env - input )
else
	env = input + RT * (env - input )

is there some advantage to the former over the latter?

also, i wondered how the author was formulating his time coefficients.  
i am using someone else's algo:

AT = e ^ ( ln (0.01) / Attack_in_samples )
RT = e ^ ( ln (0,01) / Release_in_samples )

i am also struggling with the concept of gain smoothing and  
"soft-knee". is this essentially implemented in the AT and RT  
coefficient equations? or is this a separate calculation that occurs  
after the control gain (gain reduction) is calculated?

getting back to RMS detection, in the linked article, the author states  
that the TAV coeff. can be equal to either AT or RT and between 0 and  
1. what if one were to create an "RMS Average" parameter, similar to  
traditional "attack" and "release" time parameters (translating from  
user input in ms to samples in the back-end), and use the above  
attack/release coeff. equations to calculate TAV. in other words:

TAV = e ^ ( ln (0.01) / RMS_average_in_samples )

and then to plug that into your RMS equation.

the aforementioned author uses a different equation for calculating AT  
and RT, which i don't quite understand. (see the section "Gain Factor  
Smoothing".) though, isn't this essentially what i'm already doing with  
my time coefficients? what if i replaced the value "0.01" with a  
parameter k, where k is between 0.01 and 1? would that effectively be a  
soft-knee parameter?


On Dec 12, 2003, at 1:09 AM, Furi Andi Karnapi wrote:

> Hi,
>
> I'm not sure about DAFX book. Anyway, the RMS measurement equation is  
> xRMS(n) = (1 - TAV).xRMS(n - 1) + TAV.x^2(n), where TAV is an  
> averaging coefficient. You need to take the square root of xRMS(n) to  
> get the RMS value.
>
> Regards,
> Furi
>
> -----------------------------------------------
> Furi Andi Karnapi
> DSP Lab S2-B4a-03
> School of EEE, Nanyang Tech. University
> Singapore 639798
> Phone: +65-6790-6901
> -----------------------------------------------
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