Should I study D. S. Processing or control theory in greater depth?

AI Thread Summary
Studying digital signal processing (DSP), applied math, and image processing/computer vision is recommended as these subjects complement each other effectively, particularly since image processing is a subset of DSP. The first subject combination offers practical applications relevant to general engineering, while operating systems architecture is seen as overly specialized with limited broader utility. Advanced mathematical control theory includes essential topics like state space control and optimal control, which are valuable in various engineering contexts. Transitioning to the first combination by dropping operating systems architecture is viewed as a beneficial choice. Overall, the selected subjects can enhance skills applicable in diverse engineering fields.
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I'm studying CE and math. My computer engineering course is basically electronic/electrical engineering with extra software. I have a choice between the two subject combinations below. Additionally, 1. I'm studying two mechatronic control theory subject, and a mathematical control theory subject1, 2. I have the option to study a PDE subject , a non-linear dynamics (chaos) subject, or a image processing/computer vision subject 3. I'm studying algorithms and data structures, and have the option to study maching learning or high performance computing. Any advice is appreciated.

Subject combination 1

Digital signal processing
Advanced digital filtering: polyphase, multirate, all-pass, lattice & IIR filters. Signal conditioning, analog filter types, sigma delta converters. Fast algorithms; Cooley-Tukey FFT, mixed radix formulations, Good-Thomas algorithm. Autoregressive, moving average signals. DSP applications and programming.

Applied math
Elements of vector analysis. Sturm-Liouville theory. Fourier transform & Green's functions. Generalised functions. Modelling with scalar & vector fields: perfect fluid flow & potential theory; convection-diffusion equations & spread of pollutants; elastic continua and vibrations.

Subject combination 2

Operating systems architecture
Implementation and design techniques for operating systems. Core material includes advanced kernel-level and device driver programming techniques, how operating systems principles are realized in practice, principles and practice of operating system support for distributed and real-time computing, case studies and different approaches to operating system design and implementation, including different models of software ownership.

Advanced mathematical control theory

Topics from: state space control; linear systems; calculus of variations & Pontryagin principle; optimal control, quadratic optimisation, Riccati equations; stability; LQG, Kalman filtering; frequency domain theory; Matrix transfer functions, realisations; coprime factorisation; robust control.

edit: I just realized I could take applied math, DSP, and image processing/computer vision and advanced control theory if I give up operating systems architecture. Is this a good idea? Do the subjects complement each other?
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1.
Calculus of variations: critical points; Euler equations; transversality; corner conditions; Hamilton equations; Jacobi equations; Legendre sufficient condition; Weierstrass E-function. Control theory: Lagrange, Mayer & Bolza problems; Pontryagin maximal principle, legendre transformations, augmented Hamiltonians, transversality, bang-bang control, linear systems.
 
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Subject combination 1 is more likely to be useful to you in general engineering practice. Operating systems architecture is so specialized only a few people profit from knowing it in detail.

Applied math, DSP, and image processing complement each other very well, especially since image processing is a branch of DSP which is similar to a lot of discrete math (with different notation, sadly).
 
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