I did a minor in mathematics a couple years ago and the non-engineering (i.e. rigorous) math I have been exposed to were two proper courses in prob and statistics, 2 courses in real analysis and 2 courses in abstract algebra, the second one covering mostly linear algebra (dual spaces, span, Cayley-Hamilton, Jordan etc.) Now I'm in EE and we get thrown a bunch of stuff at our faces and I seem to be the only one being like, hey, guys, where are those formulas coming from. So I would like to carry on getting a good underlying understanding. For example the Laplace and Fourier transforms are used extensively, as well as the dirac and other generalized functions. I'm having courses in signal processing and control theory right now and have found while talking to profs that having a good math background would be a great asset to get research internships as the other guys have no idea what analysis is for the most part and would be lost in a more advanced context. So I am trying to turn that year in pure math into an engineering asset (also, hey, I like to understand stuff I manipulate everyday), be it not the most in depth knowledge of the different topics(e.g.category theory) I would like to get solid ground in the following:
Real analysis: I have read Bertolt and Sherbert cover to cover back in math but I think I need more now
Operator theory and distribution theory which I think would be included in any advanced real analysis book along with measure theory and maybe a tiny bit of topology
Chaos theory and non linear systems stuff for control systems. For example linearization of odes for state space representation
Furthering the algebra can't be bad, but is Dummit and Foote really the only way to go, I got to admit it intimidates me
By the way I realized I won't have time to grasp all that in the month, I am only trying to come up with a list of references as I get more wtf moments. (the most urgent being the distribution stuff, seriously, in EE we basically spend all our time playing with the dirac) Also I know the question for self studying is redundant and has many duplicates however I think my specific case has the following characteristics which make it relevant : transferred to EE, EE has some very specific mathematical tools that it needs (e.g. once again distribution theory, when people don't even grasp complex numbers is already introduced via circuit theory) also I would like my learning to be structured in such a way that it backs up the tools I use as I progress and use more subtle stuff. For example right now in control theory linearization of state space is simply done by taking first derivatives (giving Jacobian matrices), so understanding the distributions would be more urgent
Thanks a lot