Electrical Engineering Courses

EE6000MEng Project6 ch
This project oriented course may include theoretical, experimental, or computer studies supervised by an ECE faculty member. A substantial written document as well as a public presentation of a completed project is required. Eligible for credit only towards the MEng degree.
EE6013Special Topics in Electrical Engineering3 ch
This course is intended to provide students an opportunity to study a topic not currently covered by other graduate courses. The course of study will be under the direction of a faculty member with appropriate expertise. An outline of the work to be completed and the means for assessment should be submitted for approval by the Director of Graduate Studies prior to registration in the course. 
EE6153VLSI Circuit Design3 ch
Based upon the undergraduate course EE4173 (Devices and Circuits for VLSI), the graduate level course expands upon devices and circuits for VLSI; introduction to circuit design and layout; CAD tools for simulation; logic gates; R.F. components and circuits.
EE6213Advanced Digital Systems 3 ch
Methods and tools for the design of FPGA-based digital circuits with focus on large-scale systems, i.e. digital signal and arithmetic processors, microcomputers. VLSI design process, standards, constraints, implementation, technology-dependent optimization, simulation, testing, and verification. Multi-FPGA systems. FPGA-based peripheral devices. One or more design projects.
EE6233Real Time Operation of Microcomputers3 ch
This course deals with operating system kernels for use in microprocessor applications. Topics covered will include problems of real time applications multitasking concepts, the design of a real time operating system kernel and consideration in multi-microprocessor systems. Introduction to real time systems operation: polling, interrupt I/O, concurrent I/O, handlers; Multitasking concepts: processes and process management, scheduling, critical sections, mutual exclusion, interprocess communication and synchronization, semaphores, monitors, message passing, deadlock; Real Time Operating System Kernels: design and implementation of KMOS, case studies, RMX, VRTX, application of a RTOS; Multi Microprocessor Systems: typical configurations, system design issues.
EE6263Foundations of Knowledge Representation for Software Eng.3 ch
The goal for this course is to study the state of the art of the approaches, paradigms, techniques, languages, techniques, languages, tools, etc. used for knowledge representation and automated reasoning in computer systems with emphasis on comparative evaluation of these approaches in the software in engineering context. Practical use of knowledge engineering tools is an integral part of this course.
EE6313Introduction to Modern Control Theory3 ch
Introduction: the control problem, open and closed loop control; Models of Dynamic Systems: linear systems, nonlinear systems, linearization; Review: Laplace transforms and transfer functions, poles and zeros, transient response, frequency response, stability, Nyquist stability criteria, root locus; Overview of Feedback Analysis and Design: trade-offs relating noise, disturbances and control energy, open and closed loop transfer functions, stability and stability margin; Feedback Synthesis: pole placement – polynomial approach, Smith predictor; Limitations of Feedback: time domain limitations, frequency domain limitations, dealing with constraints; Controller Architectures: internal model, reference feedforward, disturbance feedforward; Advanced Controllers: synthesis using Q parameterization, design based on optimization.
EE6323Digital Control Systems 3 ch
This course will cover topics in classical control system design, feedforward and feedback control, stability, performance, robustness and sensitivity, sampled data control systems. Sampled signals, the Nyguist sampling Theorem, reconstruction, aliasing and anti-aliasing filters. Digital control systems analysis, discrete time models of continuous time plants, effect of transportation delay, reachability, controllability and observability, mapping of system poles and zeros, transmission zeros, frequency response in sampled data systems, multi-rate sampling. Digital translation of analog controllers. Analysis techniques in sampled data control systems, stability, noise and disturbance rejection, unmodelled dynamics. Digital control system design, state space techniques, dynamic pole placement techniques. Digital control system implementation issues, architecture, quantization, coefficient wordlength, execution speed.
EE6333Topics in Control3 ch
We will invesitgate a wide range of tools and methods in the design, analysis, optimization and control of systems to prepare students for the modern control systems. MATLAB will be the software plateform. The control Theory will be applied to design applications for unmanned systems. This course focuses on theoretical and practical control problems. In addition to discussing the deployed systems, some future directions are given. Topics to be discussed include research results in system identification, sensor fusion, state estimation, navigation, linear control, and non linear control, etc.
EE6343Advanced Robotics and Autonomous Systems 3 ch
This course is offered to graduate students and final year undergraduate students. Research in robotics and autonomous ground vehicles has been more and more extensive. There are many theoretical findings and real-world applications of robotics and autonomous systems in the industry. This course will introduce the general prinicples of robotics and autonomous systems. Students will learn modeling, kinmeatics, dynamics, sensing, planning and control of robotics and autonomous system at the graduate level. Students who successfully complete this course will be able to conduct research in autonomous systems, sensing, planning and control of robotic systems, such as robot manipulators and unmanned ground vehicles.
EE6353Multivariable Feedback Design3 ch
Pre-requisite of EE6313. This course will enable design of real control systems by gaining a fundamental understanding of performance and rubustness in multivariable control systems. The course will give an overview of classical control system design for scalar systems. The multivariable interpretation of poles, zeros and the Nyquist stability criteria will be described. Performance and robustness will be characterized using singular values. The LQCG and H‡ design methodologies will be discussed.
EE6363Applied Haptics3 ch

Haptics is the science and technology of experiencing and creating touch sensations in human operators. This course will cover the three interrelated domains of human physiology, mechanisms, and control, to develop kinaesthetic and tactile haptic displays that render a variety of environments. Course content consists of equal parts of at-home reading, in-class instruction of theoretical concepts, and in-lab application. Students in this course are required to design, fabricate, and control their own haptic device. Students cannot receive credit for both EE6363 and ECE 4343.

EE6373Signal Processing Architecture3 ch
This courses stresses the practical issues of implementing digital signal processing algorithms on current hardware, including: sampling rate and processing requirements; binary fixed and floating point representations; IEEE floating point format; the Intel 8087 numeric processor extension; high level languages and digital signal processing; a survey of current DSP architectures; the Texas Instruments TMS320C30 processor; interfacing C language with assembly language; and various applications of digital signal processing. Students may be required to prepare a project, written report and in-class presentation. Pre-requisites: courses in DSP.
EE6383Nonlinear Control Systems 3 ch
Context of linear systems methods in nonlinear world. Equilibria and small signal linearization. Singularity analysis. Bifurcations and center manifold theory. Digital simulation of deterministic and stochastic nonlinear systems. Lyapunov stability definition and theorems. Absolute stability theorems. Sinusoidal input describing function methods for analysis and design. Random input describing function methods for analysis. Thorough industrial and multi disciplinary applications are stressed.
EE6413Power System Optimization3 ch
After first introducing the fundamentals of power system optimization, the classic model of optimization with contraints is covered and extended to transmission system with losses, and to hydro-thermal power systems. Various methematial solution techniques are presented including first and second order gradient, and dynamic programming. Unit commitment is a significant course component. Active power and reactive power optimal power flows (OPS) solutions are obtained. Deregulation and evolving market structures are covered, as well as market processes such as market clearing prices.
EE6433Protective Relaying of Power Systems 3 ch
IEEE device numbers, types of faults, fault calculation methodology, data requirements and analysis, introduction to relaying, relaying operating principles, current and voltage transformers, over current protection of transmission lines, distance protection of transmission lines, pilot protection of transmission lines, rotating machinery protection, transformer protection, bus protection, reactor and capacitor protection, protection aspects of power system phenomena (breaker failure, lightning, switching urges, loss of synchronism due to system disturbance), monitoring performance of power systems (fault graph analysis, fault location determination),
EE6443Power System Stability3 ch
Power system stability is the examination of the trajectory of the power system as it moves from an initial steady state to a new steady state (hopefully), following a disturbance. When power systems suffer a disturbance such as the loss of large generating station, the rotors of the remaining generators start to swing with respect to each other. There are various nonlinearities in the power system, included saturation, valve limits, controller ramp rates and controller limits. Power systems must stay in synchronism, otherwise islanding and potential blackout can occur. Fortunately there is an inherent synchronizing force which tends to keep ac systems in synchronism. However reach machine rotor inertia, as well as the controller parameter settings for each turbine-generator, can have an interactive effect on other parts of the power system. The various nonlinearities in the power system have an influence on the stability trajectory during the first, and subsequent, swings of the rotors of the generators. The preferred method for power system stability analysis is through time simulation. Simulation is widely used by utilities around the world. The detailed models required, the large data requirement, the geographical extent of the transmission grid, and the large number of generators involved make this a complex problem. Topics include: the elementary mathematical model relating to stability, system response to disturbances, the synchronous machine, the simulation of the synchronous machine, linear models of the synchronous machine, excitation systems, effects of excitation on stability, multimachine systems with constant impedance loads, speed governing, steam turbine prime movers, hydraulic turbine prime movers, combustion turbine and combined cycle power plants.
EE6453Load Flow Analysis1.5 ch
A project based learning course which will cover topics in power system load flow calculation techniques by digital computation, phase shifters decoupled load flow, power flow equations, new FACTS – flexible AC transmission devices. Students may be required to submit a project or projects with in-class presentations.
EE6463Power Systems Dynamics3 ch
Disturbances, including loss of lines and generators and significant changes in system load, are a normal part of power system operation. When a disturbance occurs, the power system moves from one steady state, through a transient period, hopefully to a new steady state. As the power system moves toward what is hopefully a new steady state, it normally enters a condition where there is linear operation. However inertias, transport lags, transmission system configuration (loss of major transmission lines), system time constants, controller time constants, and controller gain settings become important in this region. If controllers are not properly set/tuned, dynamic instability may occur.The preferred method for analysis of power system dynamics is an eigenvalue analysis. Since the power system occupies such a large geographical area, and since there may be hundreds of eigenvalues involved, the dynamic instability may occur. The preferred method for analysis of power system dynamics is an eigenvalue analysis. Since the power system occupies such a large geographical area, and since there may be hundreds of eigenvalues involved, dynamic analysis becomes very complex. Topics include: introduction to the power system stability problem, synchronous machine modeling and theory, synchronous machine parameters, synchronous machine representation in stability studies, ac transmission, power system loads, excitation systems, prime movers and energy supply systems, high voltage direct current transmission, control of active and reactive power, small signal stability, transient stability, voltage stability, subsynchronous oscillations, mid term and long term stability, and methods of improving stability
EE6473Operations of HVDC Systems 1.5 ch
Advantages of HVDC transmission, economics, terminal station components and system configurations, bridge and valve operation and control, harmonic generation and removal, reactive power requirements, and HVDC faults and protection. Interference associated with HVDC systems.
EE6483Power System Operation and Control 1.5 ch
Operations and control functions and hierarchies in power systems, security and adequacy, capabilities and constraint of power system components, primary and secondary control of frequency, MW and MVAR flow control, load curves, unit commitment, introduction to optimization methods. 
EE6493Fuzzy Sets and Applications to Engineering3 ch
This course is aimed to teach various aspects of fuzzy set theory including Fuzzy sets basic operations; types of fuzzy sets; fuzzy operators for union, intersection and aggregation; fuzzy extension; fuzzy graphs, fuzzy relations and fuzzy calculus. The course will also discuss several applications to power systems fuzzy power flow, fuzzy LP, fuzzy OPF, fuzzy based scheduling methods and fuzzy EP methods.
EE6503Topics in Artificial Neural Networks3 ch
This course is intended as an introduction to some of the more popular neural network paradigms; the paradigms discussed will include both feedforward and feedback structures as well as both supervised and unsupervised training algorithms. Emphasis will be placed on the engineering aspects of these systems as opposed to their biological plausibility. A large percentage of the course will be devoted to the theory which underlies the paradigms; applications will also be discussed. From this course, students should gain an appreciation for gradient descent and other optimization algorithms, higher dimensional geometry, multivariate calculus.
EE6513Introduction to Random Variables and Stochastic Processes3 ch
This course will include topics in probability; random variables; stochastic processes; linear systems with random inputs; minimum mean squared error design of filters; measurement and analysis of random data; and an introduction to estimation.
EE6514Wireless Communications3 ch
This course includes: the basics of mobile radio telephone, mobile telephone frequency channels, components of mobile radio, objective of mobile telephony, major problems and tools available, mobile radio environment, fading and propagation loss, loss prediction, channel and signal models, fading statistics, classification of fading, frequency reuse, cellular concept, interference standards.
EE6523Detection and Estimation Theory3 ch
Topics for this course will cover Detection: binary hypotheses, Bayes decision criteria, risk decision space, performance, MAP receivers, M-ary hypotheses; Estimation: Bayes estimation; MMSE, MAP, ML estimators, performance, Cramer-Rao inequality, efficient estimators, multiple parameters estimation; General Gaussian detection and estimation; Random process characterization: Karhunen – Loeve expansion, Gaussian process, white processes, Wave form communication: wave form detection, matched filter, performance, FSK, PSK, ASK waveform parameter estimation. Prerequisite: EE6513 .
EE6533Topics in Communication 3 ch
This course will cover various topics in communication theory and systems as suits the research interests of the students. Possible topics may include wireless communications (including cellular concepts; large scale path loss; small scale path loss; fading; minimum mean square error design of filters).
EE6543Adaptive Filtering3 ch
Topics will cover discrete time stochastic processes; stochastic state space models; Yule-Walker equations; stationary discrete time stochastic processes; characterization of stochastic processes; correlation matrix; power spectral density; least square estimation; minimum variance and linear minimum variance estimation, orthogonality and projection; the normal equation; minimum mean-squared error; optimum non recursive filter; optimum recursive filter; Kalman filter; innovation sequence; adaptive algorithms; finite impulse response filters; recursive least-squares algorithms, least mean squares adaptive algorithm; steepest gradient; Newton and Conjugate gradient algorithms; etc.; noise cancellation; inverse modeling; identification
EE6553Digital Image Processing 3 ch
A study of some fundamental concepts in digital image processing. Topics include: spatial image enhancement; processing imagery using Fourier transforms; image restoration; wavelet theory; image segmentation and image feature description. Prerequisites: some signal processing background is preferable.
EE6563Time Series Analysis3 ch

Time series, or sequential data, are widely encountered in industry and in research, including areas such as healthcare, IoT, smart grid, economics, biological signals, and virtually any sampled signal. This course introduces concepts in signal processing, machine learning, and deep learning for time series analysis and forecasting. Course delivery combines instruction, independent learning, assignments, and term projects. 

Prerequisites: ECE 3511, STAT 2593, ECE 4553.
EE6573Spread Spectrum Communications3 ch
Spread spectrum systems. Frequency hopping and direct sequence. Pseudo-Random Binary sequences. Bandwidth considerations. Synchronization and Correlators. Code tracking loops. Noise and jamming. Various applications of spread spectrum. Students are expected to prepare a project based on an approved topic in modern spread spectrum communications. The project may deal with a specific commercial product or application but should emphasize the specific technical aspects involved. Projects will be presented in class at the end of term. A written report is due the last day of classes. Reports will be graded for presentation, technical content, and overall appreciation of the concepts covered in this course.
EE6602Industrial Electronics3 ch
This graduate course will cover the design, structure, and principles of operating various switch-mode and resonant power electronic converters (PECs), along with their control techniques. Over the past few decades, there have been growing industrial demands for different PECs in a wide range of applications, including power systems, renewable energy systems. These demands have created needs for designing new topologies and controllers (convential and intelligent) that can offer accurate, efficient, and economic performances. This course aimes to cover several types and topologies of PECs and their controllers. Moreover, this course will cover designing and modeling different controllers in different reference frames, which can simplify the implementation of controlled PECs. The Industrial Electronics graduate course is a lecture-based one that has design cases, projects and term papers. Also, this course will include labs as parts of the projects and term papers works. Finally, the course will provide students with practice to conduct literature reviews, search for articles, and practice writing technical papers. There will be one class test and a final exam. This course includes the following topics: advanced switch-mode PECs, resonant PECs , reference frame transformations, controllers for PECs, digital and micro-processor implementations, standards and industry practices for operation PECs.
EE6603Renewal Energy Systems3 ch
Renewable energy sources include solar, wind, ocean currents, tidal waves, geo-thermal, and biomass. A conversion system is required to utilize renewable energy for supplying separate loads and/or into connecting to utility grids. This course aims to cover several types of renewable energy conversion and utilization systems. It is a lecture-based course with design cases, project and term papers. Also, this course will include labs as parts of the projects and term paper works. There will be one class test and a final exam. Current and industrial renewable energy system sizing, system design, modeling and control will be covered in the course. The course includes the following topics: introduction to Wind Energy Conversion Systems (WECS), assessment of wind energy potential, types of WECS, wind turbines modeling and control strategies, stand-alone and grid connected WECS systems, hybrid energy systems, energy storage, solar energy systems, photovoltaic cells, module and array concepts, PV system design and operation, stand-alone systems, grid connected systems, PV sizing and maximum power tracking, micro-hydro electrochemical system and control, introduction to tidal power, wave energy converters, ocean current systems and hybrid  energy system sizing.
EE6653Power Electronics3 ch
This course will cover topics in power semiconductor devices; rectifiers; AC voltage controllers; DC-DC converters (choppers); DC-AC converters (inverters); and electric motor drives.

EE6663Smart Grid Technologies and Operation3 ch
This course offers graduate students an opportunity to expand their knowledge on smart power systems and to work with smart grid tools and technologies. The course aims to provide a comprehensive understanding of the smart grid: its heterogeneity, dynamics, control, security, and assessment strategies. The course content covers a wide range of topics and is designed to integrate knowledge from various disciplines such as electrical power systems, communication technologies, and mathematics. Students will develop independent projects that use third party smart grid tools to develop or enhance smart grid systems and techniques.
EE6673Data Analytics for the Smart Grid3 ch
This course covers the fundamentals of Smart Grid Analytics, which combines data science, machine learning, and statistical analysis techniques to improve the efficiency, reliability, and security of power systems. The course includes an overview of the Smart Grid concept, the challenges, and opportunities of Big Data in the energy sector, the principles of data analytics, and the use of analytics for grid optimization, forecasting, fault detection, and demand response.
EE6733Simulation and Digital Analysis of Signals3 ch
This course is intended for a wide audience including electrical and computer engineering students as well as geodesy and geomatics, computer science, science and kinesiology students. Opportunities in the context of simulation and signal analysis will be provided for students to practice simple but sound software engineering technique to ensure quality in research-oriented software development. Opportunities will be made available for both skilled and novice programmers to enhance their software engineering skills. Students with strong signals background can focus on their efforts on complicated simulation and analysis problems, automated data manipulation in the context of their own discipline, amd statistical analysis digitally manipulated data. All simulation and analysis will be performed in Matlab.
EE6823Advanced Antenna Theory3 ch
For graduate students in the area of antennas and electromagnetic wave propagation. Students are expected to be familiar in these areas. This course builds upon the foundation of introductory antenna theory with advanced aspects of wave propagation and antenna theory including array analysis and synthesis, wave guiding and dispersion, magnetic and electric sources, impressed, induced and equivalent sources, images, duality, basic theorems and computation techniques.
EE6853Microwave Measurements3 ch
This graduate level microwave measurements course involves the completion of lengthy and detailed laboratory experiments on microwave devices and systems. Students should have an undergraduate level exposure to electromagnetics theory and basic microwave principles. Experiments will be conducted on measuring dielectric properties of materials, S-parameters, microwave leakage, equivalent circuits of microwave devices, microwave power and properties of microwave systems and devices.
EE6863Wireless Power Transfer3 ch
The core concepts of wireless power transfer are introduced, and the current state of the art is explored in terms of existing specifications, standards, and emerging technologies. Course material intersects the areas of power electronics and electromagnetics. High-speed power inverter and rectifier topologies are explored, along with concepts such as zero voltage switching and load independence. Coupled mode theory and radio-frequency network analysis are applied to model the wireless interface. Coil, electrode, and antenna design considerations are presented in the context of power transfer efficiency, electromagnetic compatibility, and radiofrequency exposure.
EE6903Topics on Design of Safety-Critical Systems 3 ch
This course studies concepts and techniques for the design of fault-tolerant computer systems used in safety-critical applications at graduate level. It provides analysis and evaluation methods to perform qualitative and quantitative analysis of safety-critical systems. The course studies different hardware and software configurations to ensure different levels of safety, reliability and availability of fault tolerant systems. It studies concepts on hazard identification, mishap mitigation, unreliability, unavailability; reparability, risk analysis, redundancy, fail-safe systems, and fail-operate computer systems with emphasis in practical applications.
EE6913Advanced Biomedical Instrumentation3 ch
This course deals with the problems and solutions encountered when applying biomedical instrumentation techniques to human subjects. The emphasis throughout the course is on the use of service electrodes however many concepts apply to other areas of instrumentation. The material is divided into six modules: the origins of biopotentials, biopotential electrodes, differential amplifier design, coupling with the environment, isolation design techniques, and low-noise instrumentation. Throughout the course the conflict between desigining for best electrical performance and ensuring patient safety is highlighted. It is expected that prospective students have a working understanding basic electrical engineering program that includes electronics. There are several scheduled labratory excersises for this course. These cover aspects of electrode modeling, differential amplifiers, common-mode interference, fly-back modulation and noise-analysis. Most of these labratories will be conducted using the pSpice circuit simulation package and will form a mandatory part of this course. Consequently. previous exposure to this popular simulation software would be beneficial. This course is given through Blackboard course delivery system and there are no scheudled face to face lectures. For those students who on the UNB campus, some additiona labratory excersises or demonstrations may be given to illustrate some of the points contained in the lecture material. These will be conducted in the Electrophysiology Labratory at the Institute of Biomedical Engineering (IBME).
EE6923Biological Signal Processes3 ch
The objectives of this course are to consider electrical signals which arise in biological systems; to consider mechanisms by which information is conveyed in biological systems; and to consider biological signal processing for a number of applications. This course will include topics in bioelectric sources; signal processes; communication processes; signal acquisition; signal processing and others.
EE6933Topics in Biomedical Engineering3 ch
A selection of topics related to Biomedical Engineering, including time-frequency analysis, pattern recognition, estimation theory, the spinal and peripheral nervous system, and electrocardiography. Prerequisite: EE 6513 or equivalent.
EE6943The Basis of Biomedical Engineering3 ch
This course is intended to provide a foundation of essential knowledge pertaining to biomedical engineering research. What is offered demonstrates much of the diversity of the field. Various faculty members from a variety of departments/faculties (disciplines) offer lectures for this course.
EE6997Master's Thesis Programcr
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EE6998PhD Thesis Programcr
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