## RMS Averaging?

Jan 03 2017 | 1:47 am
I'm looking for a gen~ alternative to average~ for rms averaging.
Anyone have a simple solution?
Thanks!

• Jan 03 2017 | 2:24 pm
``````// Gen RMS calculator.
// henszimmerman@gmail.com.

// Input buffer.
Delay input(8192, 1, feedback=0);

// Amount of samples to average.
Param n;

// Accumulator.
acc = 0;

// Step through all samples.
for(idx = 0; idx < n; idx += 1)
{
// Read next value from input buffer.

// Add square of value to accumulator.
acc += (v * v);
}

// Store next value we read from the input.
input.write(in1);

// Output RMS of n samples.
out1 = sqrt(acc / n);

``````
• Jan 03 2017 | 4:09 pm
Nice one!
• Jan 03 2017 | 4:19 pm
This is perfect, thanks HZ37!
• Jan 03 2017 | 5:19 pm
Hello , can u say , if i do at first sqrt(pow(in,2)) and after do averange - is that right ?
• Jan 03 2017 | 7:38 pm
Hello , can u say , if i do at first sqrt(pow(in,2)) and after do averange – is that right ?
no.
• Jan 03 2017 | 7:42 pm
// Gen RMS calculator. // henszimmerman@gmail.com. ...
while this works correctly, it gets insanely expensive for larger averaging windows. i would propose something like the code below. caveat: averaging size is fixed, as i don't know an easy way to reset a delay line in gen~. you could make it work with a buffer, though.
Delay d(2000); History y(0); n = 2000; rdiv = 1 / n;
sq = in1 * in1; xn = d.read(n, interp="none"); avg = sq + y - xn;
out1 = sqrt(avg*rdiv);
y = avg; d.write(sq);
• Jan 04 2017 | 3:00 am
for many applications you might want to/can downsample the analysis. in this particular situation the order rms->average can make sense.
• Jun 06 2017 | 6:11 pm
Does HZ37's code provide RMS updated every sample, whereas Volker Böhm's code provides RMS value only every 2000 samples?
A continous RMS, updated per sample, would be more desirable for example for a peak versus RMS comparison, threshold measurement and such.
Thanx for any insight!