Very cool! Today I messed with 4seq and I have 8-Bit Cipher in the queue... I find these modules very 'nice' but I may need some time to discover their advantages. I will watch your other videos to get to know you better. Thanks!
Cool! Thats pretty interesting and inspiring. The interesting part comes from feedback. I'm sure that these systems can be described by an already existing mathematical toolkit which I'm not familiar with. After a quick Wiki search ( think of the articles 'Nonlinear filter' or 'Nonlinear system' ) I already found some interesting things. I think it would be pretty interesting to implement a generic parametrizable neuron in PD as well. Keep up the good work!
Thanks! I actually have a couple videos building neurons in Pd (ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-PdJG5SFmVaw.htmlsi=ZZEaJ7uXsBLxGzf3). Lots of fun stuff to play with!
Another great use for this module is to obtain the max and min of two signals. Just take the positive output and add back the negative input for max. For min invert the positive output and add back the positive input. Cheers!
Just patched this up, looks like you can also obtain the min by taking the max configuration and switching the positive output with the negative, and the max by doing the same thing in the min configuration. I hope it makes sense!
Yes, another way to express this would be... Max = (half rectify (A - B)) + B Min = (invert (half rectify (A - B))) + A Or in words (as if you were patching it)... Take two signals (A and B), Mult and invert one copy of signal B. Sum that with signal A. Half rectify this. Sum the result with the copy of original (non-inverted) signal B for max. To find the min, you'd want to invert a copy of the half rectified sum (A - B) and sum that with a copy A.
