From what I gather, the Laplace Transform transforms a function f(t) into a function f(s). I'm not entirely sure what "s" is supposed to be though... I suspect it is used as a temporary placeholder for going inbetween different Laplace transforms or something, but the videos weren't very clear.
An eigenvector is a vector which can either be transformed by a certain matrix or multiplied by a certain scalar and result in the same vector in both cases. The scalar is called the eigenvalue.
I also found out that the class I started going through was apparently not a prereq for the Convex Optimization classes. I seem to have misread the prereqs, effectively "putting the comma in the wrong spot". I'm not going to complain about having less on my plate though!
Speaking of having less on my plate; I seem to have spoken too soon. Earlier today I remembered that Chris Hecker has a page listing resources for learning how to simulate physics, located here: http://chrishecker.com/Physics_References Now that I have a bit more experience, I decided to give it another look. I think it might be good idea to go through the steps he describes, so I will be looking into getting the first book in a month or so. In the meantime, I ordered some books on graph theory, abstract algebra, and topology. These should keep me busy for at least a month, and they cover topics I have been curious about for a while.
Reposted from http://invisiblegdev.blogspot.com/
I haven't done any Laplace transforms since college, but as I recall it was used extensively in control theory - how is it used in the image processing domain??