I guess I can get the coefficients and derive an overall gain parameter. I got objects in ELSE that do that [coeff2pz]. But if it also depends on the frequency I should calculate this all of the time which doesn't seem reasonable. Maybe just keeping a safe 0.5 q is fine...
You know, using something like lop~ is pretty stable, I am now wondering if I should just use if for the sake of simplicity and efficiency as well. Do I really need a 6db decay per octave instead of 3db? What do you people think?
will make some tests...
thanks
Em qua., 27 de abr. de 2022 às 09:11, José de Abreu abreubacelar@gmail.com escreveu:
sorry, but I'm very curious. Using a resonance filter implies phase shifting right? (instead of using a non resonance linear phase filter) But this means that the tuning of the KS will be affected only near the resonance? i may not understand this fully, but I never thought about using resonance inside KS
Em qua., 27 de abr. de 2022 08:51, Claude Heiland-Allen < claude@mathr.co.uk> escreveu:
Hi Alexandre,
On 27/04/2022 06:01, Alexandre Torres Porres wrote:
hi list, I'm using a 2nd order lowpass resonant filter whose coefficients I'm getting from the famous Eq-cookbook and using it inside a feedback loop to implement karplus-strong.
I also have a coded object for that (pluck~) and the 'q' parameter is 0.5, which is a "safe" setting, i.e. the filter doesn't get unstable and blows up.
The filter in isolation should be stable for any positive 'q', but its gain might get bigger than 1 making the larger feedback loop explode.
You can do some additional gain reduction if increasing the q factor increases the peak gain of the filter and makes the feedback loop explode.
I was now trying to find a higher 'q' coefficient but it's hard to know where I can go "exactly" just under it could blow up.
You want the total gain in the feedback loop for all frequencies to be less than 1, i.e. peak (over frequencies) gain less than 1.
Is there an easy way to know this other than trial and error?
The filter gain probably depends on cut-off frequency as well as q, so the filter peak gain is a function of 2 parameters. Maybe gathering numerical data and surface-fitting a mathematical function could work, if the maths to do it analytically is too hard.
If you modulate the filter parameters, it could still explode (the filter theory as per eq cookbook is only valid for fixed parameters, afaik).
If you implement with insufficient accuracy inside the filter feedback (e.g. single precision floating point for 'y' in a biquad implementation), rounding errors can accumulate and can affect the actual gain (vs the theoretical gain you'd get from exact maths).
Claude
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