Non-linear
Some recent images from my ongoing Brain Activities:
Watching a nice video of a beach

Listening to classical music

Listening to The Prodigy

Looking at Reddit's /r/gore

The two measurements are fractal dimension and sample entropy. I'm told they're both kinds of nonlinear analysis, though I confess the definition of nonlinear somewhat escaped me. Speaking of non-linear, the algorithm I'm using for calculating sample entropy is ridiculously slow. I think it's at least n2, maybe worse. There's apparently a faster version using magical K-D trees but it's not very well described anywhere and the maths is a bit over my head.
However, maybe I can just ditch sample entropy entirely for another entropy measurement. I've recently learned that you can get a very robust entropy measurement by just zipping your data and taking the ratio of the compressed to uncompressed size.