My to-the-point question: If I were to pick between rigour-based real analysis, rigour-based complex analysis or linear programming/optimization, which one would be the most beneficial for pursuing graduate studies in communication systems? My mathematical background: - All the typical EE maths (Calculus up to Vector Calc, ODEs, PDEs, Fourier analysis) - Mathematical proofs (relearning calculus using sigmas and deltas, proofs, sets, axioms, convergence, etc) - Intro to complex analysis (non-rigorous, mostly just calculations) - Intro Statistics and Probability - Applied PDEs and Numerical Analysis I am going into my last year of Electrical Engineering and plan on pursuing graduate studies in communication systems or a related field. I have the option of taking one or two graduate courses in my last semester of study. However, professors of these courses all recommend or require certain math prerequisites. For example, a course in stochastic signals requires a working knowledge of fundamental rigour-based real analysis with recommended knowledge of measure theory. A course in modern control systems strictly imposes a formal course in rigour-based complex analysis as its requirement. Another course in internet communication systems highly recommends previous experience in linear programming and mathematics typical for a CompSci student (graph theory, algorithm complexity, etc). From what I can gather, even though all of these courses are in the same general field, their pre-reqs are completely different. Of course, an actual graduate student will probably not tackle all of these areas of study and will only have select math pre-reqs. For me, I am not sure what I actually want to focus on and would like to keep options open.