BiquadPeak

A Biquadratic Peaking Filter

(?signal,?f1,0.5,48)BiquadPeak  Normalise  !signal1

(?signal1,?f1,0.5,48)BiquadPeak Normalise  !signal1

(?signal1,?f1,0.2,48)BiquadPeak Normalise  !signal1

The above will make a tone like sounds form white noise.

(?signal,?centre-frequency,?q,?gain)BiquadPeak 

BiquadPeak is an IIR filter which filters just a peak. It is different form BandPass in that BandPass produces clean linearly slowed sides to the pass bands when graphed in DBs. Peak produces a sigmoidal side. The peak width can be very narrow or very broad, this is controlled by q. ?gain controls the amount the top/center of the peak is in increased amplitude compared to signal at a arbitrary distance from the that centre. The centre is naturally controlled bu centre-frequency. 

Amazingly Handy Document - RBJ EQ CookBook

A Huge thanks to Robert Bristow-Johnson for having written released this VERY useful document!

         Cookbook formulae for audio EQ biquad filter coefficients
----------------------------------------------------------------------------
           by Robert Bristow-Johnson  <rbj@audioimagination.com>


All filter transfer functions were derived from analog prototypes (that
are shown below for each EQ filter type) and had been digitized using the
Bilinear Transform.  BLT frequency warping has been taken into account for
both significant frequency relocation (this is the normal "prewarping" that
is necessary when using the BLT) and for bandwidth readjustment (since the
bandwidth is compressed when mapped from analog to digital using the BLT).

First, given a biquad transfer function defined as:

            b0 + b1*z^-1 + b2*z^-2
    H(z) = ------------------------                                  (Eq 1)
            a0 + a1*z^-1 + a2*z^-2

This shows 6 coefficients instead of 5 so, depending on your architechture,
you will likely normalize a0 to be 1 and perhaps also b0 to 1 (and collect
that into an overall gain coefficient).  Then your transfer function would
look like:

            (b0/a0) + (b1/a0)*z^-1 + (b2/a0)*z^-2
    H(z) = ---------------------------------------                   (Eq 2)
               1 + (a1/a0)*z^-1 + (a2/a0)*z^-2

or

                      1 + (b1/b0)*z^-1 + (b2/b0)*z^-2
    H(z) = (b0/a0) * ---------------------------------               (Eq 3)
                      1 + (a1/a0)*z^-1 + (a2/a0)*z^-2


The most straight forward implementation would be the "Direct Form 1"
(Eq 2):

    y[n] = (b0/a0)*x[n] + (b1/a0)*x[n-1] + (b2/a0)*x[n-2]
                        - (a1/a0)*y[n-1] - (a2/a0)*y[n-2]            (Eq 4)

This is probably both the best and the easiest method to implement in the
56K and other fixed-point or floating-point architechtures with a double
wide accumulator.



Begin with these user defined parameters:

    Fs (the sampling frequency)

    f0 ("wherever it's happenin', man."  Center Frequency or
        Corner Frequency, or shelf midpoint frequency, depending
        on which filter type.  The "significant frequency".)

    dBgain (used only for peaking and shelving filters)

    Q (the EE kind of definition, except for peakingEQ in which A*Q is
        the classic EE Q.  That adjustment in definition was made so that
        a boost of N dB followed by a cut of N dB for identical Q and
        f0/Fs results in a precisely flat unity gain filter or "wire".)

     _or_ BW, the bandwidth in octaves (between -3 dB frequencies for BPF
        and notch or between midpoint (dBgain/2) gain frequencies for
        peaking EQ)

     _or_ S, a "shelf slope" parameter (for shelving EQ only).  When S = 1,
        the shelf slope is as steep as it can be and remain monotonically
        increasing or decreasing gain with frequency.  The shelf slope, in
        dB/octave, remains proportional to S for all other values for a
        fixed f0/Fs and dBgain.



Then compute a few intermediate variables:

    A  = sqrt( 10^(dBgain/20) )
       =       10^(dBgain/40)     (for peaking and shelving EQ filters only)

    w0 = 2*pi*f0/Fs

    cos(w0)
    sin(w0)

    alpha = sin(w0)/(2*Q)                                       (case: Q)
          = sin(w0)*sinh( ln(2)/2 * BW * w0/sin(w0) )           (case: BW)
          = sin(w0)/2 * sqrt( (A + 1/A)*(1/S - 1) + 2 )         (case: S)

        FYI: The relationship between bandwidth and Q is
             1/Q = 2*sinh(ln(2)/2*BW*w0/sin(w0))     (digital filter w BLT)
        or   1/Q = 2*sinh(ln(2)/2*BW)             (analog filter prototype)

        The relationship between shelf slope and Q is
             1/Q = sqrt((A + 1/A)*(1/S - 1) + 2)

    2*sqrt(A)*alpha  =  sin(w0) * sqrt( (A^2 + 1)*(1/S - 1) + 2*A )
        is a handy intermediate variable for shelving EQ filters.


Finally, compute the coefficients for whichever filter type you want:
   (The analog prototypes, H(s), are shown for each filter
        type for normalized frequency.)


LPF:        H(s) = 1 / (s^2 + s/Q + 1)

            b0 =  (1 - cos(w0))/2
            b1 =   1 - cos(w0)
            b2 =  (1 - cos(w0))/2
            a0 =   1 + alpha
            a1 =  -2*cos(w0)
            a2 =   1 - alpha



HPF:        H(s) = s^2 / (s^2 + s/Q + 1)

            b0 =  (1 + cos(w0))/2
            b1 = -(1 + cos(w0))
            b2 =  (1 + cos(w0))/2
            a0 =   1 + alpha
            a1 =  -2*cos(w0)
            a2 =   1 - alpha



BPF:        H(s) = s / (s^2 + s/Q + 1)  (constant skirt gain, peak gain = Q)

            b0 =   sin(w0)/2  =   Q*alpha
            b1 =   0
            b2 =  -sin(w0)/2  =  -Q*alpha
            a0 =   1 + alpha
            a1 =  -2*cos(w0)
            a2 =   1 - alpha


BPF:        H(s) = (s/Q) / (s^2 + s/Q + 1)      (constant 0 dB peak gain)

            b0 =   alpha
            b1 =   0
            b2 =  -alpha
            a0 =   1 + alpha
            a1 =  -2*cos(w0)
            a2 =   1 - alpha



notch:      H(s) = (s^2 + 1) / (s^2 + s/Q + 1)

            b0 =   1
            b1 =  -2*cos(w0)
            b2 =   1
            a0 =   1 + alpha
            a1 =  -2*cos(w0)
            a2 =   1 - alpha



APF:        H(s) = (s^2 - s/Q + 1) / (s^2 + s/Q + 1)

            b0 =   1 - alpha
            b1 =  -2*cos(w0)
            b2 =   1 + alpha
            a0 =   1 + alpha
            a1 =  -2*cos(w0)
            a2 =   1 - alpha



peakingEQ:  H(s) = (s^2 + s*(A/Q) + 1) / (s^2 + s/(A*Q) + 1)

            b0 =   1 + alpha*A
            b1 =  -2*cos(w0)
            b2 =   1 - alpha*A
            a0 =   1 + alpha/A
            a1 =  -2*cos(w0)
            a2 =   1 - alpha/A



lowShelf: H(s) = A * (s^2 + (sqrt(A)/Q)*s + A)/(A*s^2 + (sqrt(A)/Q)*s + 1)

            b0 =    A*( (A+1) - (A-1)*cos(w0) + 2*sqrt(A)*alpha )
            b1 =  2*A*( (A-1) - (A+1)*cos(w0)                   )
            b2 =    A*( (A+1) - (A-1)*cos(w0) - 2*sqrt(A)*alpha )
            a0 =        (A+1) + (A-1)*cos(w0) + 2*sqrt(A)*alpha
            a1 =   -2*( (A-1) + (A+1)*cos(w0)                   )
            a2 =        (A+1) + (A-1)*cos(w0) - 2*sqrt(A)*alpha



highShelf: H(s) = A * (A*s^2 + (sqrt(A)/Q)*s + 1)/(s^2 + (sqrt(A)/Q)*s + A)

            b0 =    A*( (A+1) + (A-1)*cos(w0) + 2*sqrt(A)*alpha )
            b1 = -2*A*( (A-1) + (A+1)*cos(w0)                   )
            b2 =    A*( (A+1) + (A-1)*cos(w0) - 2*sqrt(A)*alpha )
            a0 =        (A+1) - (A-1)*cos(w0) + 2*sqrt(A)*alpha
            a1 =    2*( (A-1) - (A+1)*cos(w0)                   )
            a2 =        (A+1) - (A-1)*cos(w0) - 2*sqrt(A)*alpha





FYI:   The bilinear transform (with compensation for frequency warping)
substitutes:

                                  1         1 - z^-1
      (normalized)   s  <--  ----------- * ----------
                              tan(w0/2)     1 + z^-1

   and makes use of these trig identities:

                     sin(w0)                               1 - cos(w0)
      tan(w0/2) = -------------           (tan(w0/2))^2 = -------------
                   1 + cos(w0)                             1 + cos(w0)


   resulting in these substitutions:


                 1 + cos(w0)     1 + 2*z^-1 + z^-2
      1    <--  ------------- * -------------------
                 1 + cos(w0)     1 + 2*z^-1 + z^-2


                 1 + cos(w0)     1 - z^-1
      s    <--  ------------- * ----------
                   sin(w0)       1 + z^-1

                                      1 + cos(w0)     1         -  z^-2
                                  =  ------------- * -------------------
                                        sin(w0)       1 + 2*z^-1 + z^-2


                 1 + cos(w0)     1 - 2*z^-1 + z^-2
      s^2  <--  ------------- * -------------------
                 1 - cos(w0)     1 + 2*z^-1 + z^-2


   The factor:

                    1 + cos(w0)
                -------------------
                 1 + 2*z^-1 + z^-2

   is common to all terms in both numerator and denominator, can be factored
   out, and thus be left out in the substitutions above resulting in:


                 1 + 2*z^-1 + z^-2
      1    <--  -------------------
                    1 + cos(w0)


                 1         -  z^-2
      s    <--  -------------------
                      sin(w0)


                 1 - 2*z^-1 + z^-2
      s^2  <--  -------------------
                    1 - cos(w0)


   In addition, all terms, numerator and denominator, can be multiplied by a
   common (sin(w0))^2 factor, finally resulting in these substitutions:


      1         <--   (1 + 2*z^-1 + z^-2) * (1 - cos(w0))

      s         <--   (1         -  z^-2) * sin(w0)

      s^2       <--   (1 - 2*z^-1 + z^-2) * (1 + cos(w0))

      1 + s^2   <--   2 * (1 - 2*cos(w0)*z^-1 + z^-2)


   The biquad coefficient formulae above come out after a little
   simplification.

Direct Filters

DirectLowPass, DirectBandPass, DirectHighPass, DirectLowPassBessel, DirectBandPassBessel, DirectHighPassBessel

These six processors represent the work horse of subtractive synthesis and general filtering. They are non resonant infinite impulse response filters with variable cut-off rates. The versions which do not end in Bessel are Butterworth filters. The Bessel ones are Bessel filters. The difference in use is that the Bessel filters introduce hardly any phase distortion in the pass band but are much shallower than the Butterworth filters. The Butterworth filtes do introduce some phase distortion but are much steeper. At the time of writing Sonic Field does not have steeper IIR filters than Butterworth because the lobes in the pass and reject bands of such filters tend to make their use problematic. For a true 'brick wall' style filter convolution is the solution. However, as the Butterworth filters will (under some conditions) go up to 10 or even 11 order and still be stable, it is hard to see why one might want a sharper filter.

High and Low Pass Layout:

(?signal,?frequency,?order)DirectXXXPass !new-signal

Band Pass:

(?signal,?low-frequency,?high-frequency,?order)DirectXXXPass !new-signal

Where XXX is Low,High or Band. Put Bessel on the end of the processor name to get the equivalent Bessel Filter. Frequency is in Hz and order can be from 1 to 11 for low and high or 1 to 5 for band. However, sometimes these filters go unstable and produce non numbers or infinities in the outgoing signal. This is more likely with high pass filters with low frequency cut-offs or band pass where the upper frequency is low or where the two frequencies are very close (closer than 10%). Reducing the order makes it less likely for a filter to go unstable. Low pass filters are almost always stable. High pass are OK at 6 orders down to around 100 Hz and order 2 and 12 Hz (usually). Band pass is less stable and order 4 is only useful for frequencies over 200 Hz. These are all approximate values, experimentation is required.

Note: the higher the order, the steeper the filter. The cut-off frequencies are the -6db points.