Pure Data Artificial Neuron Patch from Scratch

Patching up an artificial neuron in Pure Data Vanilla for some nonlinear mixing. There’s no talking on this one, just building the patch, and listening to it go.

An artificial neuron is basically just a mixer: inputs come in, and are weighted differently, modelling the dendrites of a biological neuron; then the mixed signal is transformed by an “activation function”, usually nonlinear, and output, modelling the axon.

Now, we can say that “learning” occurs when we adjust the weights (levels) of the inputs based on the output, but let’s not do that here, let’s just revel in our our nonlinear mix.

More details in my blog post here

0:00 Nonlinear Mixing and Artificial Neurons
1:17 Adding “Bias”
2:28 Neuron Complete
3:27 Automating the Weights
7:09 Adding Feedback
8:42 Adding Noise
9:58 Commenting our Code
11:25 Trying the ReLU Activation Function
12:04 Linear Mixing (with Hard Clipping)

Pure Data introductory tutorials here
More no-talking Pure Data jams and patch-from-scratch videos

No-Input DAW (Logic Pro X Feedback Loops & Sound Design)

Tutorial on “no-input mixing” in a DAW (Logic Pro X, in this case) for wild feedback-based sound design.

With a little knowledge of digital signal flow, we can easily set up an aux track in our DAW as a feedback loop–sending the track back into itself. Once we start adding effects, we can achieve new and unexpected sounds. This technique could be a way to generate some new sonic material, add some interest to a drum loop, or even generate vast, evolving soundscapes.

0:00 Intro / Casio Beat
0:39 Output to Aux Track
1:06 Feeding Back with a Bus Send
2:20 Adding Effects to the Loop
4:14 More Subtle Effects
4:58 More Extreme (Pitch Shifter)
5:17 Removing the “Input”
6:47 Talking through the No-Input Mixer
8:18 Closing Thoughts

More Logic Pro X tutorials: