After a lot of gyrations, you end up with variations on Fourier Transforms. In other words, translate from waves to spectra and back. It's more fun if you can apply it to sound or image processing. If you are a glutton for punishment, go look at wavelets. Fourier transforms define events in terms of continuous waves, but that leaves inconvenient side bands.
Wavelets use little blips of waves as the basis, allowing much tidier modeling of single events.
Here you get to do everything you've learned so far all over again, but with complex numbers. To be honest, I didn't complete all the sections. So scan the text, then find some numerical analysis texts, and implement your own library as a learning exercise. Generally this is taught as Operations Research in MBA classes. You might want to implement simplex.