The world is full of examples of cyclical phenomena. Large cycles include planetary motion, seasons, tides, and ocean waves. Societies are governed by cycles: empires rise and fall, economies boom and bust, and fashion keeps repeating itself. On an individual scale, the human lifecycle, eating and sleeping, heartbeats and breathing, and locomotion are all periodic. And so are sound and light, the very nature of the world we percieve.
Wouldn't it be nice to understand and manipulate cyclical phenomena? A couple hundred years ago, Fourier showed that any repeating periodic signal, regardless of its complexity, can be represented as a sum of sine functions, paving the way for much deeper signal understanding. More recently, Shannon showed that you can take analog signals and represent them as numbers, which brings us to digital signal processing. For modifying digital signals, we need to look to digital filters.
Inspired by Dick Lyon's book (https://www.amazon.com/Human-Machine-Hearing-Extracting-Meaning/dp/1107007534), I made an explorable explanation that lets you play with digital filters visually. I'd like to present it as a demo or talk at WAC 2018.
Here's a blog post about it: http://smus.com/filter-playground/
Here's the demo itself: https://borismus.github.io/filter-playground/?equation=%28z%29%2F%28z-0.7585034463554621%29
And here's a video: https://www.youtube.com/watch?v=6OIOTpQYsts