After identifying an area of interest, choose courses that are of interest and meet the guidelines given in your program.
Simply stated, you must meet each condition given in those guidelines for a particular degree. For example, if you are pursuing a Coursework MS, you must have 18 credits minimum of 5000-6000 AND 12 credits maximum 4000 series courses AND 3 credits maximum of EE 5805. That is, you should "logically AND" each of the requirements in a given list. Courses chosen from other engineering disciplines—math, physics, or materials science—are all permitted. Within the ECE department, recommended course sequences are given below
Electrophysics
Basic Courses: Taught Every Year
A mathematically rigorous study of dynamic electromagnetic fields, beginning with Maxwell's equations. Topics include scalar and vector potentials, waves, and radiation.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer
- Pre-Requisite(s): EE 3140
Rigorous study of nonlinear optics, anisotropic, optical materials, dielectric waveguides, directional couplers, semiconductor optics, light sources, lasers, and photodetectors.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
- Pre-Requisite(s): EE 3090 or PH 3210 or EE 4411
A study of the physical principles of electronic materials, their applications in solid-state devices, and future trends in their development.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
A study of the physical principles and evolution of solid-state devices, such as transistors: from conventional to novel types utilizing hetero-junctions and quantum effects; light emitting devices, semiconductor lasers; and displays of various types.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring
- Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
Advanced Courses: Usually Taught Every Other Year
Risk assessment and vulnerabilities for industrial control environments including electrical power grids. Cyber-physical attack tools and techniques. Interaction of cybersecurity issues with physical systems and physical security. Limitations of current cybersecurity technologies. Design and cost considerations for various defensive methods.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring
- Restrictions: Permission of instructor required
- Pre-Requisite(s): EE 3120
This course will cover advanced topics dealing with MEIXIS technologies, transduction mechanisms, and microfabricated sensors and actuators.
- Credits: 4.0
- Lec-Rec-Lab: (3-1-0)
- Semesters Offered: Spring
- Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
- Pre-Requisite(s): EE 4240 or MY 4240
Topics include: basics of radiation theory, Hertzian dipole and loop antennas, near and far fields, bandwidth, gain and other antenna parameters, Yagi-Uda, bow-tie, cavity-backed and traveling wave antennas, microstrip solutions, miniaturization, substrates and superstrates.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, in odd years
- Pre-Requisite(s): EE 5526
Computer Engineering
Basic Courses: Taught Every Year
Building blocks of wireless sensor networks, sensor node design, wireless communications, network protocols, data storage and retrieval, sensor localization and clock synchronization. Example application areas: robotics, autonomous vehicles and networks, power engineering, smart-grid, environment monitoring, and disaster relief.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Pre-Requisite(s): (CS 4461 or EE 4272 or EE 5722) and (EE 3170 or EE 3173) and (CS 1129 or CS 2141)
This course introduces embedded control system design using a model-based approach. Course topics include model-based embedded control system design, discrete-event control, sensors, actuators, electronic control unit, digital controller design, and communication protocols. Prior knowledge of hybrid electric vehicles is highly recommended.
- Credits: 3.0
- Lec-Rec-Lab: (0-2-2)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following College(s): College of Engineering; Must be enrolled in one of the following Major(s): Electrical Engineering, Mechatronics, Electrical & Computer Engineer
- Pre-Requisite(s): MEEM 4700 or MEEM 4775 or EE 3261 or EE 4261
Nanoscale chip design presents issues for IC designs and new market areas for design automation. This course provides a comprehensive introduction on layout design. Advanced algorithms and optimization techniques are presented to give students the skills needed for nanometer VLSI design.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): CS 4321 and EE 4271
Advanced Courses: Usually Taught Every Other Year
Building blocks of wireless sensor networks, sensor node design, wireless communications, network protocols, data storage and retrieval, sensor localization and clock synchronization. Example application areas: robotics, autonomous vehicles and networks, power engineering, smart-grid, environment monitoring, and disaster relief.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Pre-Requisite(s): (CS 4461 or EE 4272 or EE 5722) and (EE 3170 or EE 3173) and (CS 1129 or CS 2141)
This course covers the four main paradigms of Computational Intelligence, viz., fuzzy systems, artificial neural networks, evolutionary computing, and swarm intelligence, and their integration to develop hybrid systems. Applications of Computational Intelligence include classification, regression, clustering, controls, robotics, etc.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Restrictions: Permission of instructor required; Must be enrolled in one of the following Level(s): Graduate
This course will explore the foundational techniques of machine learning. Topics are pulled from the areas of unsupervised and supervised learning. Specific methods covered include naive Bayes, decision trees, support vector machine (SVMs), ensemble, and clustering methods.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring
- Restrictions: Permission of instructor required; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
Signals and Systems
Basic Courses: Taught Every Year
Theory of probability, random variables, and stochastic processes, with applications in electrical and computer engineering. Probability measure and probability spaces. Random variables, distributions, expectations. Random vectors and sequences. Stochastic processes, including Gaussian and Poisson processes. Stochastic processes in linear systems. Markov chains and related topics.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
Overview of linear algebra, Modern Control: state-space based design of linear systems, observability, controllability, pole placement, observer design, stability theory of linear time-varying systems, Lyapunov stability, optimal control, Linear Quadratic regulator, Kalman filter, Introduction to robust control.
- Credits: 3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical & Computer Engineer
- Pre-Requisite(s): EE 3261 or MEEM 3750
Detecting and estimating signals in the presence of noise. Optimal receiver design. Applications in communications, signal processing, and radar.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall, Spring
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering
- Pre-Requisite(s): EE 5500
This course focuses on the basic principles that underlie the analysis and design of digital communication systems. Topics covered include: characterization of communication signals and systems, modulation schemes, optimum receiver design and performance analysis in AWGN and band-limited channels, concepts of information theory and channel coding, carrier and symbol synchronization, and ISI channel equalization.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 4250
Advanced Courses: Usually Taught Every Other Year
Introduction to the mathematical foundations for information theory, inference and learning algorithms. Topics include data compression, channel coding, Bayesian inference, clustering, marginalization, Monte-Carlo methods, Markov models, and Bayesian learning networks.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, Summer, in odd years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 5500(C)
Fundamentals of image processing are covered including image representation, geometric transformations, binary image processing, compression, space and frequency domain processing. Computer programming in MATLAB and Python required.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall, Spring
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical & Computer Engineer, Electrical Engineering, Computer Engineering
Principles of wireless communications systems. Projects may include cell phones, computer networks, paging systems, satellite communications, radio, television and telemetry.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 5527
Basics of microwave engineering. Topics include: microwave sources; wave equations and their solutions; wave propagation; reflection, and guiding; transmission line theory and practice; microwave network analysis and impedance matching; microwave resonators, filters, and dividers; left-handed materials and devices.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall, Spring
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 3140 or EE 5140
Topics include: basics of radiation theory, Hertzian dipole and loop antennas, near and far fields, bandwidth, gain and other antenna parameters, Yagi-Uda, bow-tie, cavity-backed and traveling wave antennas, microstrip solutions, miniaturization, substrates and superstrates.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, in odd years
- Pre-Requisite(s): EE 5526
Building blocks of wireless sensor networks, sensor node design, wireless communications, network protocols, data storage and retrieval, sensor localization and clock synchronization. Example application areas: robotics, autonomous vehicles and networks, power engineering, smart-grid, environment monitoring, and disaster relief.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Pre-Requisite(s): (CS 4461 or EE 4272 or EE 5722) and (EE 3170 or EE 3173) and (CS 1129 or CS 2141)
This course introduces embedded control system design using a model-based approach. Course topics include model-based embedded control system design, discrete-event control, sensors, actuators, electronic control unit, digital controller design, and communication protocols. Prior knowledge of hybrid electric vehicles is highly recommended.
- Credits: 3.0
- Lec-Rec-Lab: (0-2-2)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following College(s): College of Engineering; Must be enrolled in one of the following Major(s): Electrical Engineering, Mechatronics, Electrical & Computer Engineer
- Pre-Requisite(s): MEEM 4700 or MEEM 4775 or EE 3261 or EE 4261
Power
Basic Courses: Taught Every Year
Advanced analysis and simulation methods for load flow, symmetrical components, short circuit studies, optimal system operation, stability, and transient analysis. Application of commonly used software reinforces concepts and provides practical insights.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
- Pre-Requisite(s): EE 4222
Specialization/Advanced Courses: Taught Every Year
Hybrid electric vehicles (HEV) will be studied and simulated using advanced powertrain component analysis and modeling. An in-depth analysis and study of power flows, losses, and energy usage are examined for isolated powertrain components and HEV configurations. Simulation tools will be developed and applied to specify powertrain and vehicle components and to develop control and calibration for a constrained optimization to vehicle technical specifications.
- Credits: 3.0
- Lec-Rec-Lab: (0-3-0)
- Semesters Offered: Spring
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following College(s): College of Engineering
- Pre-Requisite(s): MEEM 4295 or EE 4295
This hands-on course examines challenges with powertrain integration in Hybrid Vehicles. Topics include Vehicle Development Process, Thermal Management, Vehicle Controls, Safety, Calibration, and Vehicle Simulation Models. The course project includes optimizing performance of a configurable HEV using modeling and experimentation.
- Credits: 3.0
- Lec-Rec-Lab: (0-2-2)
- Semesters Offered: Spring, Summer
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following College(s): College of Engineering
- Pre-Requisite(s): MEEM 4296(C) or EE 4296(C)
These courses are also co-listed as mechanical engineering courses.
Advanced Courses: Usually Taught Every Other Year
A study of transient behaviors and their analysis and prediction. Addresses analytical methods and their numerical implementation, switching and lightning surges, short circuits, and non-linear effects. Includes computer simulations.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, in odd years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer; May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
- Pre-Requisite(s): EE 4222
Advanced electromechanics of rotating and linear machines. Topics include dynamic analysis of machines, reference frame transformations, reduced order models, models of mechanical loads, power electric drives for motors, and digital simulation of machines and electric drive systems. Applications discussed will include renewable energy and electric propulsion systems.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall, in odd years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
Real-time monitoring and protection of modern power systems. Secure and reliable operation of radial and grid systems. Protection of transmission lines, buses, generators, motors, transformers, and other equipment against disturbances.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, in odd years
Theory-based application of software and hardware used for power system protection. Fault simulations, protective relay settings and coordination, and test operation of relays under static, dynamic, and transient conditions.
- Credits: 1.0
- Lec-Rec-Lab: (0-0-2)
- Semesters Offered: Spring, in odd years
- Pre-Requisite(s): EE 5223(C)
Advanced topics of circuits for electrical energy processing. Covers switching converter principles for dc-dc, ac-dc, and dc-ac power conversion. Other topics include harmonics, pulse-width modulation, classical feedback control, nonlinear control, magnetic components, power semiconductors, and digital simulation.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Fall, in odd years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 4227
Topics include modeling and computer methods applied to electrical power systems, matrix formulations, network topology and sparse matrix data structures, load flow, short- circuit and stability formulations, constrained optimization methods for load flow and state estimation, and time-domain simulation methods for transient analysis.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, in odd years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical & Computer Engineer
- Pre-Requisite(s): EE 5200
Modeling and analysis of electrical distribution systems; load characteristics, load modeling, unbalanced three-phase overhead and underground line models, and distribution transformers. Analysis of primary system design, applications for capacitors, voltage drop, power loss, distribution system protection, and introduction to advanced distribution automation.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: Spring, Summer, in odd years
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 4221
Advanced Courses: Usually Taught Every Third Year
Study of advanced engineering and economic algorithms and analysis techniques for the planning, operation, and control of the electric power system from generation through transmission to distribution.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Restrictions: Must be enrolled in one of the following Level(s): Graduate; Must be enrolled in one of the following Major(s): Electrical Engineering, Electrical Engineering, Electrical & Computer Engineer
Wind turbines are the fastest growing segment of the generator mix being added to power systems today. There is a growing need to understand the many issues caused by these additions. This course covers the theoretical background, regulations, integration experience, and modeling.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Restrictions: May not be enrolled in one of the following Class(es): Freshman, Sophomore, Junior
A study of the dynamic behavior of power systems. A review of synchronous machine modeling, system dynamic equations, and method of analysis. Examines overall system behavior via small signal and transient stability and energy functions. Also studies voltage stability and non-linear effects.
- Credits: 3.0
- Lec-Rec-Lab: (3-0-0)
- Semesters Offered: On Demand
- Restrictions: Must be enrolled in one of the following Level(s): Graduate
- Pre-Requisite(s): EE 5200