Is there any rule of thumb for choosing MUSIC FILTER algorithm?

Development
1

I mean, I know FIR, IIR, etc. But I am not sure which exact algorithm I should use.

Anyone knows, say which filter algorithm SuperCollider RLPF is using?

Thanks in advance.

3

interesting! are there any UGen implementations of the Trapezoidal SVF out there that anyone knows of?

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4

I’m making a tiny application with a GUI and using the filters as I see on textbooks like the Cookbook. It is clear this is just trying to have a working program, using the simplest solutions.

something likle

lowPassFilter :: Float -> Float -> IIRParams
lowPassFilter freq q =
    IIRParams
        { b0
        , b1 = 1 - cos w0
        , b2 = b0
        , a0 = 1 + α
        , a1 = -2 * cos w0
        , a2 = 1 - α
        }
  where
    b0 = (1 - cos w0) / 2
    w0 = calcW0 freq
    α = calcAQ w0 q

But, now tell me, is it true all good information about filters is dispersed everywhere in papers? Is there a place where we get all the information, but also get music insights like you usually share here? Show us the way!

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5

@nathan maybe that’s still one of the most " basic" filters, but what are the materials you would try? Even the Faust code is kind of messy, or just normal?

That’s the " Constant Peak-Gain Resonator"

6

This is a pretty thorough overview of many filter architectures. Not for musical insights though…

Luckily, there’s code for all of it:

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7 
% Function Match example usage: Match(0.75)
function Match(wc)
    wc = wc * pi; % Convert cutoff frequency using pi

    figure(1); % Open a figure window
    hold on; % Hold on to plot multiple graphs

    % Bilinear transform calculations
    Gc = sqrt(1/2);
    alpha = tan(wc/2) / sqrt(1/(Gc*Gc) - 1);
    b = [alpha, alpha];
    a = [1+alpha, alpha-1];
    [h1, w] = freqz(b, a, 2048); % Frequency response

    % Gain adjustments
    g1 = 2 / sqrt(4 + (2*pi/wc)^2);
    gm = max(sqrt(0.5), sqrt(g1));

    % Analog-matched transform calculations
    Ws = tan(wc * sqrt(1 - gm^2) / (2 * gm)) * sqrt((gm^2 - g1^2) * (1 - gm^2)) / (1 - gm^2);
    b0 = Ws + g1;
    b1 = Ws - g1;
    a0 = Ws + 1;
    a1 = Ws - 1;
    b = [b0/a0, b1/a0];
    a = [1, a1/a0];
    [h2, w] = freqz(b, a, 2048); % Frequency response

    % Analog prototype filter
    num = 1; 
    den = [1/wc, 1]; 
    h3 = freqs(num, den, w); % Frequency response

    % Plotting
    plot(w/pi, abs(h1).*abs(h1), 'r', ...
         w/pi, abs(h2).*abs(h2), 'b', ...
         w/pi, abs(h3).*abs(h3), 'g'); % Plot frequency responses

    % Adding labels and legend
    xlabel('Normalized frequency (x\pi rad/sample)');
    ylabel('Square magnitude');
    legend('Bilinear transform', 'Analog-matched transform', 'Analog prototype');
end
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