Course Descriptions

Explores issues involving safety and environmental concerns in the context of the practice of electrical and computer engineering.

Weekly hours: 1 Lecture hours
Restriction(s): Restricted to students in the Electrical Engineering and Computer Engineering programs.

The solution and understanding of engineering problems and system behavior will be studied with emphasis on implementation using computer-based methods. Topics include numerical modeling, roots and optimization, linear algebra, solving systems of equations, numerical integration and differentiation, solving differential equations, basic probability, statistics, distributions, expectation, and curve fitting. A computer laboratory is an important element of the class.

Weekly hours: 3 Lecture hours and 1.5 Practicum/Lab hours
Prerequisite(s): MATH 134 or (MATH 123 and MATH 124).

Introduction to solid state electronics. Emphasis is on circuit design concepts with extensive discussion on diodes and diode circuits and on bipolar junction transistors (BJT) and field effect transistors (FET) as amplifiers and as switches.

Prerequisite(s) or Corequisite(s): GE 153 or EP 202.
Note:Students with credit for EP 311 will not receive credit for this course.

An introduction to digital logic including combinational and sequential logic devices and circuits. Covers the range from the fundamentals of Boolean algebra and the binary number systems to combinational and sequential circuit functional blocks such as adders, multiplexers, counters and state machines. Some coverage is also given to electronic characteristics of real logic devices and field programmable gate arrays (FPGA).

Prerequisite(s): GE 152 or EE 221.

This course introduces the fundamentals and building blocks of power systems. Topics include; power in the sinusoidal steady state; single- and three-phase transformers.

Prerequisite(s): (MATH 134 or (MATH 123 and MATH 124)) and (GE 153 or EP 202).
Note:Students with credit for EE 212 will not receive credit for this course.

Introduces the fundamental concepts and techniques for the modeling and analysis of discrete-time signals and linear systems. Topics include: sinusoids and complex exponential representation, Fourier series, sampling, reconstruction, discrete-time representation of signals and systems, linear time invariant (LTI) systems, finite impulse response (FIR) filters, frequency response, z-transforms, infinite impulse response (IIR) filters and Fourier analysis. MATLAB is introduced using simulation-based laboratories that explore analysis tools and their applications.

Weekly hours: 3 Lecture hours and 1.5 Practicum/Lab hours
Prerequisite(s): ((GE 152 and MATH 134) or (MATH 123 and MATH 124)) and (CMPT 142 or CMPT 116 or CMPT 141).
Note:Students with credit for EE 351 will not receive credit for this course.

Basic concepts in materials science, crystals, kinetic theory, heat capacity, thermal fluctuations, Boltzmann equation, x-ray diffraction, crystal imperfections, solid solutions, alloys, mechanical properties, electrical properties, thermal properties, heat transport by thermal conduction, radiation and convection; and applications of these concepts in electrical engineering. Practicum and design based on these topics.

Weekly hours: 3 Lecture hours and .5 Tutorial hours
Prerequisite(s): (CHEM 146 or CHEM 114) and (PHYS 156 (taken) or PHYS 155 (taken)).
Note:Students with credit for EP 271 will not receive credit for this course.

Covers the fundamental laws governing electric and magnetic fields and some applications. Topics include static electric fields, Gauss's law, static magnetic fields, Ampere's law, time-varying fields, Faraday's law, Maxwell's equations, electromagnetic waves, interactions between fields and materials, and transmission lines. A vector calculus approach is used throughout.

Weekly hours: 3 Lecture hours
Prerequisite(s): EP 202, MATH 223 or MATH 225 or MATH 276 and MATH 224 or MATH 226 or MATH 238.
Note: This course is open to Geophysics students in the Department of Geological Sciences.

Topics include frequency response and the role of feedback in electronic circuits, differential and multistage MOS and BJT amplifiers, real operational amplifier characteristics, instrumentation amplifiers, active filters, oscillators, waveform generation circuits and power supplies. Transducers, noise and noise reductions techniques, and measurement theory and standards are also covered, along with analog and digital interfacing circuits.

Weekly hours: 3 Lecture hours and 3 Practicum/Lab hours
Prerequisite(s): EP 214, EE 221 and EE 232.
Note: Students with credit for EE 323 or EP 313 will not receive credit for this course.

Focuses on practical realization of microwave and radio frequency circuits, with emphasis on both passive and active design. Topics include network analysis, transmission line theory, impedance matching and tuning, filters, couplers, power dividers, amplifiers, and oscillators. Circuit design and performance optimization will be done using computer-aided design software.

Weekly hours: 3 Lecture hours and 2 Practicum/Lab hours
Prerequisite(s): EE 301 or PHYS 356.
Note: Students with credit for EE 402 will not receive credit for this course.

Covers the steady-state theory of electric machines. Topics include induction machines-equivalent circuit, efficiency, operating characteristics, starting, speed control and induction generator principle; synchronous machines- equivalent circuit, efficiency, operating characteristics, motor characteristics and speed control; DC machines operation, efficiency, shunt and series machines, speed control, starting.

Prerequisite(s): EE 241.

This course introduces the components of a modern power system; series impedance and shunt admittance calculations of single- and three-phase transmission lines; current and voltage relations on a transmission lines; transmission lines modeling and steady state operation; transmission line series and shunt compensations; per-unit system and single-line diagrams; corona; transmission line transients.

Prerequisite(s): EE 241.

This course discusses the fundamental concepts and introduces the essentials of analyses and design of power electronic circuits. Topics include power electronics 2 devices, switching losses, analyses and design of single-phase ac-dc converters, analyses and design of three-phase ac-dc converters, analyses and design of dc-dc converters, analyses and design of single- and three-phase dc-ac converters.

Weekly hours: 3 Lecture hours and 1.5 Practicum/Lab hours
Prerequisite(s): EE 221.
Prerequisite(s) or Corequisite(s): EE 341.
Note:Students with credit for EE 344 or EE 443 will not receive credit for this course.

This course covers the basic theory of discrete-time signal processing with linear time invariant (LTI) systems. The systems are primarily analyzed in the frequency domain, which means emphasis is placed on the z-transform of discrete-time signal as well as the system function for and frequency response of discrete-time systems.

Prerequisite(s): EP 214 and EE 265.

The intent of this course is to instill in the students the cost-performance tradeoffs associated with implementing mathematical functions/concepts with digital circuits. This course is designed to give the students intuition on the practicality of implementing mathematical functions and concepts in digital hardware. Gaining such intuition is a necessary first step toward synthesizing block diagrams for digital systems. This course explains how to represent digital signals and implement important algorithms/circuits with finite-precision arithmetic.

Prerequisite(s): CME 341 and EE 362.

This course introduces the fundamental concepts and techniques of autonomous mobile robotics. Topics include Robot Operating System (ROS) basics, mobile robot kinematics, coordinate frame transformations, mobile robot sensors (e.g., accelerometers, gyroscopes, magnetometers, scanning laser rangefinder, camera), path planning, and fundamentals of digital signal processing.

Weekly hours: 3 Lecture hours
Prerequisite(s): EE 265.3 and CMPT 214.3

This course is a hands-on introduction to the Robot Operating System (ROS) and a number of tools commonly used in robots. The focus is on autonomous mobile robotics. Students learn how to create the software that is used to interface to mobile robot sensors and actuators and implement motion control algorithms. They then debug their software using ROS tools and test it using simulation tools and finally implement their software on a mobile robot.

Weekly hours: 3 Lecture hours
Prerequisite(s): EE 367.3

Topics include mathematical modeling of control elements and systems, performance analysis, stability assessment and system compensation. Both time domain and frequency domain techniques are used. Multivariable processes are discussed using state-space models. Controller design methods specific to phase lead/lag compensators are presented using root-locus and frequency response. Control-law design using state-space is discussed. MATLAB control tools are used in computer simulations and in various analyses of control systems.

Weekly hours: 3 Lecture hours and 1 Tutorial hours
Prerequisite(s): (EP 214 and EE 265) or (EP 320 and MATH 331)
Note: Students with credit for EE 481 will not receive credit for this course.

This course covers in depth the topics: 1-Analysis of faulted power systems which includes bus impedance and admittance matrices; network equations in matrix form; symmetrical components; sequence networks; balanced and unbalanced faults, 2- Load flow studies; the static load flow equations, classification of system buses, Gauss-Seidel and Newton-Raphson methods, 3- Power system stability; modeling of the synchronous machine during transients; swing equation; equal area criterion; digital computer solution of the swing equations; small signal stability, 4- Smart grid.

Prerequisite(s): EE 342.
Note: Students with credit for EE 860 will not receive credit for this course.

Economic dispatch: lossless case, inequality constraints, participation factors, transmission system effects, penalty factors, unit commitment, electricity markets, renewable power management, solution methods; power system control: the control loops, automatic load frequency control, automatic voltage regulator, control of renewable energy; and protection: circuit breakers, protection of lines, transformers, generators, and renewable energy systems. Synchrophasor and AI applications. Simulation programs (e.g. PowerWorld, PSCAD/EMTDC) are used for the laboratories.

Prerequisite(s) or Corequisite(s): EE 441 and 382.

Covers salient-pole synchronous machines; solar photovoltaic (PV) power technology including the equivalent circuit of PV cells, characteristics of PV modules and arrays, PV current-voltage (I-V) curves and shading impacts on I-V curves, stand-alone and grid-connected PV systems, PV powered water pumping; wind power technology including types of wind turbines and wind turbine generators, assessment of power in the wind, wind turbine power curves, estimating wind turbine energy production, wind farms; energy storage; renewable energy integration and microgrids; and various renewable energy conversion systems.

Restriction(s): Restricted to students in the B.E. in Electrical Engineering program.
Prerequisite(s): EE 441
Note: Students with credit for EE 498 "Renewable Energy and Power Systems" offered in 2020-21 and 2021-22 or EE 848 may not receive credit for this course.

Examines the transmission of information (voice, video or data) over a noisy channel and presents the ideas and techniques fundamental to digital communication systems. Emphasis is placed on system design goals and the need for trade-offs among basic 2 system parameters such as signal-to-noise ratio, probability of error, and bandwidth expenditure. Topics include binary baseband/passband data transmission, M-ary modulation techniques (QPSK, OQPSK, MSK, M-ASK, M-PSK, M-QAM and MFSK), signaling over band limited channels and methods to deal with ISI, and signaling over channels with amplitude and phase uncertainties.

Prerequisite(s): EE 365.

This course covers several techniques for designing and implementing digital filters with the primary objective of minimizing the number of multipliers used in the filters. The course gives insight into the effects of finite word length arithmetic on the performance of filters.

Prerequisite(s): EE 365.

This course falls under the category of “guided design”. The students are guided through the design and implementation of the algorithms needed to control an autonomous mobile robot used to accomplish a specified task. The specific mobile robot system that is designed in this course will change from time to time as necessary to maintain relevancy.

Weekly hours: 3 Lecture hours
Prerequisite(s): EE 467.3 and EE 469.3

This course falls into the category of "guided design". The students will be guided through the design and implementation of a complex DSP-based system. The course covers the application specific theory as well as the application specific implementation issues for a specific DSP-based system. The specific DSP system that is designed in this course will change from time to time as necessary to maintain relevancy. The current design problem is a digital communication system based on quadrature amplitude modulation. The students will be guided through the design of the system, design of the modulator, the modelling of the channel and the design of the demodulator.

Weekly hours: 3 Lecture hours and 3 Practicum/Lab hours
Prerequisite(s): EE 456.3 and EE 461.3

This course introduces the fundamental concepts and techniques of digital image processing, concentrating on aspects of image processing in which both the inputs and outputs are images. Topics include image sampling and quantization, intensity transformation, spatial filtering, frequency domain filtering, image restoration and image reconstruction. The laboratory component focuses on the digital hardware implementation of image acquisition and image manipulation.

Weekly hours: 3 Lecture hours and 1.5 Practicum/Lab hours
Prerequisite(s): EE 367.3.

This course focuses on aspects of digital image processing/computer vision where the inputs are images and the outputs are attributes extracted from those images. Topics include colour image processing, image compression, basic morphological image processing, edge detection, thresholding, region detection, feature extraction, and image pattern classification. The laboratory component focuses on the digital hardware implementation of attribute extraction algorithms.

Weekly hours: 3 Lecture hours and 1.5 Practicum/Lab hours
Prerequisite(s): EE 368.3 and EE 466.3
Prerequisite(s) or Corequisite(s): EE 469.3

This course falls into the category of ’guided design’. The students will be guided through the design and implementation, in digital hardware, of a complex computer vision system. The course covers the application specific theory as well as the application specific implementation issues for a specific computer vision system. The specific computer vision system that is designed in this course will change from time to time as necessary to maintain relevancy. The current design problem is a parking lot license plate recognition system. The students will be guided through the design of the system, design of one or more circuits suitable for detection and segmentation of the license plate, design of one or more circuits suitable for license plate character extraction and normalization, and design of one or more circuits suitable for license plate character recognition.

Weekly hours: 3 Lecture hours and 3 Practicum/Lab hours
Prerequisite(s): EE 467.

This course covers some of the more advanced concepts and techniques of autonomous mobile robotics. The primary focus of the course is mobile robot mapping, probabilistic based localization, and mobile robot motion control including techniques for vision-based control.

Weekly hours: 3 Lecture hours
Prerequisite(s): EE 368.3 and EE 382.3
Prerequisite(s) or Corequisite(s): EE 467.3

A multidisciplinary introduction to the processing of micro and nano scale structures that are applied in emerging fields of high resolution patterning such as micro/nano electronics, photonics and fluidics. Fundamental technology issues including materials, instrumentation, fabrication, and inspection are discussed. Lectures are complemented by a mandatory laboratory component performed in a research laboratory. Laboratory access requires successful completion of safety training offered at the beginning of the course.

Weekly hours: 3 Lecture hours and 2 Practicum/Lab hours
Prerequisite(s): EE 271 or EP 317 or ME 214.

Topics include physical optics, Gaussian beams, thin film optics, Fabry-Perotresonators, diffraction, dielectric planar waveguides, optical fibers in optical communications, dispersion, bit-rate and bandwidth, direct and indirect semiconductors, E-k diagrams, semiconductor device principles, hetero junctions, light emitting devices, stimulated emission, Einstein coefficients for lasing devices, gas lasers, semiconductor lasers, new solid state lasers, emitters for optical communications, photodetectors, heterojunction photodiodes, noise in detectors, photodetectors for optical communications, polarization, Fresnel's ellipsoid, birefringence, light modulation, nonlinear effects, Pockels effect and modulators.

Weekly hours: 3 Lecture hours and 2 Practicum/Lab hours
Prerequisite(s): (EE 473 and EE 301) or (EP 317 and PHYS 456).
Note:Students with credit for EP 431 will not receive credit for this course.

Covers quantum physics, Schroedinger's equation, quantized energy levels, quantum numbers, photons, stimulated emission and lasers, bonding, energy bands, electron statistics, intrinsic and extrinsic semiconductors, and the physics of the pn junction and pn junction devices such as solar cells, bipolar junction transistor, junction field-effect transistor, and metal-oxide semiconductor field-effect transistor.

Weekly hours: 3 Lecture hours and 0.5 Practicum/Lab hours
Prerequisite(s): EE 271 and EE 301 (taken).
Note: Students with credit for EE 372 will not receive credit for this course.

Emphasizes the application of a formal design process. Students are divided into working groups of two or three to design, in a top down fashion, a product or system. The students start from a layman's statement of what is needed and produce a requirement specification, system analysis and specification, block level design and a working unit. The students are required to give a formal oral presentation of their year's work to a group of their peers.

Weekly hours: 6 Practicum/Lab hours
Prerequisite(s): EE Program Core and 12 credit units from the EE Program Focus Areas.
Prerequisite(s) or Corequisite(s): 9 additional credit units from the EE Program Focus Areas.

Offered occasionally to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

Weekly hours: 3 Lecture hours

This class covers FPGA and logic synthesis, instruction set architecture, ALU, data path and control, memory system design, I/O interfacing and advanced computer architecture.

Weekly hours: 3 Lecture hours

The class introduces the radiation environments mainly space and ground level, and the radiation effects on the integrated circuits. The mitigation approaches at circuit and system levels will be introduced and discussed. The mitigation techniques to be studied include temporal and spatial redundancy for logic gates, storage cells, and digital systems.

Prerequisite(s): CME 342.3, or the knowledge in digital integrated circuit design.

A study of semiconductor devices with special emphasis placed on device operation in VLSI circuits. Topics include device physics, electrical characteristics, computer simulation of circuits, speed-power-area considerations, circuit synthesis and CMOS integrated circuit design. Additional lecture topics as requested may be given. A design project is also required.

Weekly hours: 3 Lecture hours

The introduction of deep learning basics and deep learning processor architecture. Includes: artificial intelligence, deep neural network, deep learning frameworks, hardware processing element design, memory system, and advanced topics for efficient deep learning processor architecture design.

Prerequisite(s): CME 433
Note: This course is a hybrid course with GE 431, and this course cannot be taken for credit after previously taking GE 431

Deterministic signal theory, noise and its physical origin, random signal theory, performance of analog and digital communication systems in the presence of noise.

Weekly hours: 3 Lecture hours

This course teaches students the basic principles of multirate digital signal processing and how to apply these principles in the design of recursive polyphase filters. The course shall also give the students experience in designing, building and debugging fundamental circuits used in communications.

Prerequisite(s): EE 461 or equivalent (EE 880 can be accepted as co-requisite in place of this prerequisite), EE 456 or equivalent (EE 810 can be accepted as corequisite in place of this prerequisite).

Practical realization of microwave devices and circuits using linear and nonlinear techniques. Topics include small signal and low noise amplifiers, power amplifiers, frequency multipliers, oscillators, RF MEMS and microwave subsystems. Emphasis is on device and circuit simulation with realistic device models and performance optimization using computer-aided design (CAD) software.

Weekly hours: 3 Lecture hours

Efficient encoding and decoding schemes for reliable transmission of digital information over noisy channels. Topics will be chosen from the following: Algebraic coding (linear block codes, cyclic codes, BCH codes, Reed-Solomon codes), Trellis coding (convolutional codes, trellis-coded modulations, Viterbi algorithm, soft-decision decoding). Turbo-like codes (turbo-codes, low-density parity-check codes, bit-interleaved coded modulation, the forward/backward algorithm, iterative decoding).

Weekly hours: 3 Lecture hours
Prerequisite(s): EE 456 or equivalent.

The goal of this course is to study the fundamentals of wireless communications, as well as to introduce the new ideas at a level accessible to the graduate student with a basic background in probability and random processes. Examples from existing wireless communications standards will be used throughout the course.

Weekly hours: 3 Lecture hours
Prerequisite(s): EE 456 and EE 845.

A multidisciplinary introduction to advanced lithographic microfabrication processes, specifically focusing on X-ray lithography (XRL) using synchrotron radiation and the LIGA process. Engineering and scientific aspects of the various process steps, as well as related applications are discussed, granting in-depth knowledge on XRL and LIGA. In addition, the course introduces students to various aspects of process technology and microcomponent layout relevant to academic research and industrial applications in microsystems and microelectronics.

Weekly hours: 3 Lecture hours
Note: Includes lecture, design project and extended visit to the Canadian Light Source.

The fundamentals of electromagnetism and its applications. Includes Maxwell's equations, multi-pole fields, electromagnetic waves, reflection and refraction, retarded potentials and radiation, dipole antennas, antenna arrays, rectangular and cylindrical waveguides, and microwave circuits.

Weekly hours: 3 Lecture hours

Review of general solid state physics. Structures and properties of materials. Structures and properties of materials. An introduction to Wave-Mechanics. Band theory of metals, semiconductors and insulators. The modern theory of solids. Electrical conduction in solids. Phonons, heat capacity and thermal conductivity. Properties of intrinsic and extrinsic semiconductors.

Weekly hours: 3 Lecture hours

Semiconductor science. Extrinsic semiconductors. Continuity equation and applications. Photoconductivity. Principles of semiconductor devices and device models (pn junction, BJT, FET).

Weekly hours: 3 Lecture hours

The aim of this course is to introduce the fundamentals of estimation theory to graduate students. In particular, the course will focus on the applications of estimation theory to signal processing. The first part of the course will cover the concept of minimum variance unbiased estimation, Cramer-Rao lower bound, best linear unbiased estimators, maximum likelihood estimation, and least square estimation. The second part of the course will focus on general and linear Bayesian estimation and Kalman filters. The course expects maturity in 1) the basics of probability and random process, 2) linear and matrix algebra.

Weekly hours: 3 Lecture hours
Prerequisite(s): Instructor permission is required.

Wave nature of light. Diffraction phenomena and gratings. Interference and interferometers. Basic theory of optical properties of solids, thins films and multilayer structures. Optical waveguides and optical fibers. Einstein A and B coefficients for stimulated emission. Gas lasers. Solid state lasers. Photodetectors. Polarization and modulation of light Birefringence. Electo-optic effects.

Weekly hours: 3 Lecture hours

Theory and practice of designing large digital circuits with Hardware description languages Verilog and VHDL. This course focuses on FPGAs as the target implementation technology. The architectures of selected FPGAs are compared and some details of some of the internal operation of the FPGA are covered.

Weekly hours: 3 Lecture hours and 1 Practicum/Lab hours
Prerequisite(s): Undergraduate Degree.
Note: Offered in the academic year 2006/2007 and alternate years thereafter.

Iterative techniques for solving non-linear equations with one variable; techniques for solving sets of linear algebraic equations using direct and iterative methods; Iterative methods for solving non-linear algebraic equations; LU factorization and application of LU matrices; eigenvalues, eigenvectors and modal transformation, solving sets of first- and second-order differential equations; optimization techniques, numerical solutions of partial differential equations.

Weekly hours: 3 Lecture hours and 3 Practicum/Lab hours

Random variables, functions of random variables, expectations, characteristic function, joint densities and distributions, sequences of random variables, concept of stochastic processes. The emphasis is on developing a working knowledge of the above theory in engineering applications.

Weekly hours: 3 Lecture hours

Covers photovoltaic (PV) power technology including equivalent circuits and characteristics of PV cells, modules and arrays, PV current-voltage (I-V) curves, stand-alone and grid-connected PV systems; wind power technology including power in the wind assessment, wind turbine power curves, wind turbine energy production estimation; energy storage; microgrids; and energy conversion systems.

Restriction(s): Departmental Approval Required
Note: Students with credit for EE 448 may not receive credit for this course.

Basic reliability concepts, elements of probability and statistical theory, application of important distributions, reliability in series, parallel and complex systems. Application of Markov chains in the evaluation of repairable system reliability. Utilization of Monte Carlo simulation in basic system reliability evaluation.

Weekly hours: 3 Lecture hours

Reliability evaluation of static and spinning generating capacity requirements. Interconnected system reliability concepts. Transmission system reliability evaluation. Determination of composite system reliability. Distribution system reliability evaluation. Incorporation of customer interruption costs in the evaluation of power system reliability worth.

Weekly hours: 3 Lecture hours

System representation and analytical techniques required for the solution of power system steady-state and transient problems. The use of digital computers in load flow, fault and stability studies is emphasized. HVdc transmission and power system control are briefly discussed.

Weekly hours: 3 Lecture hours
Note: Students with credit for EE 441 will not receive credit for this course.

Principles of digital image processing and compression in both spatial and spectral domain including image enhancements, denoising and digital filtering techniques. Transform coding and JPEG codec. Fundamentals of digital video processing and compression in temporal domain including motion estimation and motion compensation. Digital video codecs including MPEG-4, H264 and HEVC.

Weekly hours: 3 Lecture hours
Departmental approval required
Restriction(s): Open to students registered in the College of Graduate and Postdoctoral Studies.

Relaying practices, numerical relaying, protective relaying algorithms, adaptive relaying, high-speed digital relaying, system relaying and control, special protection schemes, remedial action schemes, transient stability protection, controlled islanding, relaying applications of traveling waves, wide area measurement system based protection, microgrid protection, artificial intelligence applications.

Weekly hours: 3 Lecture hours

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

Offered occasionally by visiting faculty and in other special situations to cover, in depth, topics that are not thoroughly covered in regularly offered courses.

A seminar is held periodically throughout the regular session during which staff and graduate students discuss current research topics. Graduate students are required to attend these seminars.

Students undertaking the project Master's degree (M.Eng.) must register in this course. It consists of independent study and investigation of a real world problem, and submission of an acceptable report on the investigation.

Students writing a Master's thesis must register for this course.

Students writing a Ph.D. thesis must register for this course.