QRST (Quasi-Random Sequence Transform)



QRST (Quasi-Random Sequence Transform

I’ve been thinking about randomness and melodic progressions recently and In addition to the probabilistic quantizer I posted, I thought I would revisit the Turing module. The Turing module produces a quasi-random sequence of bits which is translated to an output value by an 8 bit DAC and scaled to 1. I decided that I wanted more control over the range and distribution of the randomness. Like the uTuring the QRST has an adjustable 1 to 16 step shift register. The ? control sets the probability that a step will change and the width sets the maximum amount of that change. There is a minimum and maximum value for the output and a center value around which the output will cluster. The distribution control sets the width of the distribution of values around the center. At minimum the output distribution will be very narrow and at maximum the distribution will be random.


Input Signal Range Notes
clock 0-1 gate the shift register moves one step with each clock
reset 0-1 gate resets the register to 0

Output Signal Range Notes
sequencer out minimum-maximum range set by min and max knobs


Control Function Notes
? sets the probability that the step will change
steps sets the number of steps from 1-16
max sets the maximum output value
center sets the center of the distribution
min sets the minimum output value
width sets the maximum change value for a step
distribution sets the width of the distribution form narrow to random


Meter Displays Notes
LED array displays the current output as a percent of the total range

Version History

Revision File Date Notes
1.0 QRST V1.0.audulus (141.5 KB) 01/21/2019 initial upload to forum


Revision File Date Notes
1.0 QRST V1.0 demo.audulus (303.4 KB) 01/21/2019 initial upload to forum
1.0 QRST V1.0 demo II.audulus (1.3 MB) 01/21/2019 this one’s higher CPU usage


Woah, this looks like a good one! can’t wait to dig in!

1 Like


Thanks. I’ve gotten a bit tired of the uTuring/uQuant combo so I’m trying a different approach. This, with the probabilistic quantizer can be a bit less random. Modulating the settings on the quantizer can lead to some interesting results. The QRST could also be useful for modulation particularly with min=0. max=1, a fairly narrow width and perhaps some slew limiting