Duluth campus

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Duluth Campus

Electrical Engineering Minor

Electrical Engineering
Swenson College of Science and Engineering
Link to a list of faculty for this program.
Contact Information
EE Graduate Program, 271 MWAH, 1023 University Drive, Duluth, MN 55812 (218-726-6830; fax: 218-726-7267)
Email: umdee@d.umn.edu
Website: https://scse.d.umn.edu/graduate-programs-5
  • Program Type: Graduate minor related to major
  • Requirements for this program are current for Spring 2023
  • Length of program in credits (master's): 6
  • Length of program in credits (doctoral): 12
  • This program does not require summer semesters for timely completion.
The Electrical Engineering minor provides students with exposure to advanced science and technologies in electrical engineering.
Program Delivery
  • via classroom (the majority of instruction is face-to-face)
Prerequisites for Admission
The preferred undergraduate GPA for admittance to the program is 3.00.
Special Application Requirements:
Students interested in the minor are strongly encouraged to confer with their major field advisor and director of graduate studies, and the Electrical Engineering director of graduate studies regarding feasibility and requirements.
For an online application or for more information about graduate education admissions, see the General Information section of this website.
Program Requirements
Use of 4xxx courses toward program requirements is permitted under certain conditions with adviser approval.
Courses offered on both the A-F and S/N grading basis must be taken A-F, with a minimum grade of C earned for each. The minimum cumulative GPA for courses applied to the minor is 3.00. Minor coursework must be approved by the Electrical Engineering director of graduate studies.
Minor Coursework (6 to 12 credits)
Master’s students select 6 credits, and doctoral students select 12 credits from the following in consultation with the Electrical Engineering director of graduate studies. Other courses can be chosen with approval of the Electrical Engineering director of graduate studies.
EE 5151 - Digital Control System Design (3.0 cr)
EE 5161 - Linear State-Space Control Systems (3.0 cr)
EE 5311 - Design of VLSI Circuits (4.0 cr)
EE 5315 - Multiprocessor-Based System Design (3.0 cr)
EE 5171 - Introduction to Robotics and Mobile Robot Control Architectures (3.0 cr)
EE 5477 - Antennas and Transmission Lines (3.0 cr)
EE 5501 - Energy Conversion System (3.0 cr)
EE 5522 - Power Electronics I (3.0 cr)
EE 5533 - Grid- Resiliency, Efficiency and Technology (3.0 cr)
EE 5741 - Digital Signal Processing (3.0 cr)
EE 5745 - Medical Imaging (3.0 cr)
EE 5765 - Modern Communication (4.0 cr)
EE 5801 - Introduction to Artificial Neural Networks (3.0 cr)
EE 8151 - Optimal Control Systems (3.0 cr)
EE 8741 - Digital Image Processing (4.0 cr)
EE 8765 {Inactive} (3.0 cr)
Program Sub-plans
Students are required to complete one of the following sub-plans.
Students may not complete the program with more than one sub-plan.
Masters
Doctoral
  
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EE 5151 - Digital Control System Design
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall & Spring
Digital control system characteristics: transient and steady-state responses, frequency response, stability. Digital control system design using transform techniques. Controllability and observability. Design of digital control systems using state-space methods: pole placement and observer design, multivariable optimal control. Implementation issues in digital control prereq: 3151; credit will not be granted if already received for 4151
EE 5161 - Linear State-Space Control Systems
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
State space representations of control systems and analysis and design. Stability, controllability, observability, realizations, state estimator or observer design and state feedback design. pre-req: 3151 or instructor consent, credit will not be granted if already received for 4161
EE 5311 - Design of VLSI Circuits
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall
This course covers custom design process of very large scale integrated circuits in CMOS technology. pre-req: EE 2212 or instructor consent
EE 5315 - Multiprocessor-Based System Design
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
Parallelism, interconnection networks, shared memory architecture, principles of scalable performance, vector computers, multiprocessors, multicomputers, dataflow architectures, and supercomputers. prereq: 2325; credit will not be granted if already received for 4315
EE 5171 - Introduction to Robotics and Mobile Robot Control Architectures
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Basic concepts and tools for the analysis, design, and control of robotic mechanisms. Topics include basic robot architecture and applications to dynamical systems, mobile mechanisms, kinematics, inverse kinematics, trajectory and motion planning, mobile roots, collision avoidance, and control architectures. prereq: 3151, credit will not be granted if already received for 4351 or 5351
EE 5477 - Antennas and Transmission Lines
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Theory and performance of antennas and transmission lines. Topics: Allocation of RF spectrum, radiation theory, EM wave propagation, ground effects, interference, antenna performance metrics, transient and sinusoidal transmission line behavior, bounce diagrams, Smith chart, waveguide theory, modeling with the numerical electromagnetics code (NEC), unlicensed wireless applications, specific antenna designs and applications, class demonstrations. prereq: 3445; credit will not be granted if already received for 4477
EE 5501 - Energy Conversion System
Credits: 3.0 [max 3.0]
Course Equivalencies: EE 5501/ME 5325
Grading Basis: A-F or Aud
Typically offered: Every Fall
Theory, design and operation of conventional and alternative electrical energy conversion systems. Carbon dioxide cycle, Earth/Sun radiation balance, and environmental impacts. Power delivery systems and integration of conversion systems with the grid. Development of generation portfolios. Impact of energy policies and current energy issues. Case studies. prereq: Chem 1151 or 1153 and 1154
EE 5522 - Power Electronics I
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Power semiconductor devices; traditional power converters; ac-dc converters: half-wave and full-wave rectifiers; dc-dc converters: traditional and transformer derived choppers; dc-ac converters: single-phase and three-phase inverters; ac-ac converters; pulse-width modulation; applications. prereq: 3235; credit will not be granted if already received for 4522
EE 5533 - Grid- Resiliency, Efficiency and Technology
Credits: 3.0 [max 3.0]
Prerequisites: 2006 or instructor consent
Grading Basis: A-F or Aud
Typically offered: Every Fall
Concepts and architecture of grid, smart grid and microgrid; resiliency under physical and cyber attacks; grid efficiency via sensors, networks and control; technology including standards and protocols for cybersecurity and protection of the grid; case studies and testbeds. prereq: 2006 or instructor consent
EE 5741 - Digital Signal Processing
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Spring
Discrete linear shift-invariant systems, z- & Fourier transform, sampling, discrete-time processing of signals, reconstruction of analog signals, filters and filter structures in direct, parallel, and cascaded forms, FIR & IIR digital filter design, impulse-invariant, bi-linear transform & window functions, FFT, introduction to image processing. prereq: 2111; credit will not be granted if already received for 4741
EE 5745 - Medical Imaging
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Spring Odd Year
Introduction to the methods and devices for medical imaging, including x-ray imaging, x-ray computer tomography (CT), nuclear medicine (single photon planar imaging, single photon emission computer tomography (SPECT), and positron emission tomography (PET), magnetic resonance imaging (MRI), and ultrasound imaging. The physics and design of systems, typical applications, medical image processing, and tomographic reconstruction. prereq: EE (ECE) 2111, Math 3298 or instructor permission
EE 5765 - Modern Communication
Credits: 4.0 [max 4.0]
Typically offered: Every Fall
Design and analysis of modern communication systems; evaluation of analog and digital modulation techniques. (3 hrs lect, 3 hrs lab) prereq: 2111; credit will not be granted if already received for 4765
EE 5801 - Introduction to Artificial Neural Networks
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Periodic Fall
General techniques and theory of neural networks, their applications and limitations. The course particularly addresses the design issues and learning algorithms for diverse areas of applications. prereq: CS 1521, Math 3280, Stat 3611 or instructor consent; credit will not be granted if already received for 4801
EE 8151 - Optimal Control Systems
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Fall Odd, Spring Even Year
Calculus of variations. Pontryagin minimum principle. Linear quadratic optimal control. Dynamic programming, Hamilton-Jacobi Bellman equation. Constrained optimal control. Linear Quadratic Gaussian control. Kalman filter. prereq: EE 5161; instructor consent
EE 8741 - Digital Image Processing
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Fall Odd Year
Mathematical foundations and practical techniques to process and manipulate images. Students will acquire the ability to analyze two-dimensional images, dealing with mathematical representation of images, image sampling and quantization, Image Transforms, Image Enhancement, Image Restoration, Image Coding, Edge Detection, Texture Analysis, and Compression. prereq: 4741