What math courses to do for control theory/signal processing?

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I am an undergraduate student majoring in math and electrical engineering. I am planning to do control theory (convex optimization) in graduate school (electrical engineering). What math courses are recommended for someone who intends to study convex optimization in graduate school?

For my math degree, I have some core math courses and some optional ones. I can not do every single math course that my university offers but I need to do the ones that would help me in graduate school to study and research convex optimization and/or signal processing.

A list of the math courses at my university can be found here.

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You can consult http://www.springer.com/la/book/9780387989457 A Course in Robust Control Theory A Convex Approach by Dullerud, Geir E., Paganini, Fernando and quickly browse through the sections in the book to gain an idea as to how convex optimization is used in control theory

Also see my answer for Self study Control Theory

Side note: The math required for control theory and signal processing are often very different. In signal processing there is more of an emphasis of doing discrete math and math involving probability. Whereas in control theory there is an emphasis of doing things in continuous time. The tools are different but there are some overlaps, optimization being one.

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Good control theory uses whatever math helps solve good and useful problems. I would say: take the controls courses that interest you, and take the math that interests you. Geometry, algebra, analysis, statistics, discrete math - they can always find their way into good engineering theory, controls most of all. We know some ways they do, but by no means all. It is by learning new things that you will find your path to a good contribution. Don't be too strict about the math that has already been used - it will show up in your controls courses anyway.

For example: control theory is NOT a branch of convex optimization, though it occasionally uses some of its tools.