Usefulness of higher math courses for EE/communication

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The discussion centers on the value of taking advanced math courses like functional analysis and abstract algebra in relation to signal processing and communication theory. While there is a plethora of applied courses available, the participants debate whether the theoretical knowledge gained from these math courses could enhance understanding in practical applications. The idea is presented that focusing on foundational courses, such as real analysis, can be beneficial, as they prepare students for self-directed learning in more complex topics. The importance of taking at least one proof-based math class is emphasized for exposure to mathematical reasoning, which can facilitate further study. Additionally, there are mentions of group theory's relevance to signal processing, suggesting that learning such topics as needed may be more effective than pursuing them solely for academic credit. Overall, the discussion weighs the benefits of theoretical knowledge against the practical demands of applied courses in engineering fields.
Gauss M.D.
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Not talking about spending all your academic credits on stuff like analytic number theory and etale cohomology or whatever, but there's a couple of math courses I'd be very interested in, if they'd be at all useful to signal processing/communication theory, namely functional analysis and abstract algebra. Of course, taking those would possibly mean foregoing some of the more applied courses (computer vision, algorithms, remote sensing and stuff like that).

Could taking those math courses ever be justified, given the vast amount of interesting applied courses available and the scarcity of available time?

There's also an advanced course in optimization that's available (I really liked the introductory course), but that's probably useful enough not to worry about, right?
 
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I don't think the mere existence of the endless applied courses means you are going to be using all of them on the job. My impression is that most jobs are not all that broad in their scope. So, I think you could make a good case that something that helps you understand something that you do use more thoroughly would be a better thing to spend your time on than one more random applied thing you won't use, unless there's some very compelling reason why you would need to add it to your skill set.

You shouldn't feel like you have to take a course if you want to learn something, though. Studying functional analysis in your own more applied way might be more useful than taking it from Mr. Abstract in the math department, depending on who's teaching and what book they use and so on. Usually, you'd want to do real analysis first, if you haven't already.

There are apparently some group theory applications in signal processing, but if I were you, my tendency would be to want to learn it as needed on my own, while keeping more of an engineering motivation than to study the subject for its own sake.

Taking at least one proof-based math class to start off with would probably be good, though, because it exposes you to that world and would prepare you to learn more mathematical material on your own. Just opens some doors.
 
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Very appreciated input, thanks.
 
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