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

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SUMMARY

The discussion centers on the choice between studying Digital Signal Processing (DSP) combined with Applied Math versus Operating Systems Architecture and Advanced Mathematical Control Theory. The consensus is that the first combination—DSP, Applied Math, and Image Processing—offers broader applications in general engineering practice. DSP encompasses advanced digital filtering techniques, fast algorithms like Cooley-Tukey FFT, and signal conditioning, while Applied Math covers essential concepts such as vector analysis and Fourier transforms. The subjects are interrelated, enhancing understanding and practical skills in engineering fields.

PREREQUISITES
  • Understanding of Digital Signal Processing (DSP) concepts
  • Familiarity with Applied Mathematics, including vector analysis and Fourier transforms
  • Basic knowledge of algorithms and data structures
  • Introduction to control theory principles and techniques
NEXT STEPS
  • Explore advanced digital filtering techniques in DSP
  • Study the applications of Fourier transforms in engineering
  • Learn about image processing techniques and their relation to DSP
  • Investigate mathematical control theory concepts such as optimal control and Kalman filtering
USEFUL FOR

Students and professionals in computer engineering, electrical engineering, and applied mathematics, particularly those interested in signal processing, control theory, and image processing applications.

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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.
 
Last edited:
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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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