An introductory course for engineering students in disciplines other than electrical or computer engineering. The course begins with a review of the concepts of resistance, capacitance, and inductance. Circuit analysis techniques are then applied to characterize the behaviour of commonly used electrical energy conversion devices such as transformers, dc machines, and induction and synchronous machines.
COURSE DELETED 2018-2019
(Lec: 3, Lab: 0.75, Tut: 0.5)

This course introduces the circuit analysis techniques which are used in subsequent courses in electronics, power, and signals and systems. Circuits containing resistance, capacitance, inductance, and independent and dependent voltage and current sources will be studied. Emphasis is placed on DC, AC, and transient analysis techniques.
(Lec: 3, Lab: 0.75, Tut: 0.5)

This is a first course on the basic concepts and applications of signals and systems analysis. Continuous time signals and systems are emphasized. Topics include: representations of continuous-time signals; linear time invariant systems; convolution, impulse response, step response; review of Laplace transforms with applications to circuit and system analysis; transfer function; frequency response and Bode plots; filtering concepts; Fourier series and Fourier transforms; signal spectra; AM modulation and demodulation; introduction to angle modulation.
(Lec: 3, Lab: 0.25, Tut: 0.5)

This course is an introduction to semiconductor electronics for students in the Electrical Engineering program and related programs. Topics studied include: operational amplifiers; dc and small signal models for diodes, basic principles of bipolar transistors and field effect transistors, dc analysis of electronic circuits and practical applications of the devices to the design of power supplies, amplifiers and digital logic circuits.
(Lec: 3, Lab: 0.75, Tut: 0.5)

Introduction to the mathematics of representing and manipulating discrete objects. Topics include numbers, modular arithmetic, counting, relations and graph theory. Methods of proof and reasoning - such as induction and mathematical logic - will also be covered. Some applications to cryptosystems, hashing functions, job scheduling, and coding will be included.
(Lec: 3, Lab: 0, Tut: 0.5)

Boolean algebra applied to digital systems; logic gates; combinational logic design; electronic circuits for logic gates; arithmetic circuits; latches and flipflops, registers and counters; synchronous sequential logic and state machine design; implementation in programmable logic chips.
(Lec: 3, Lab: 0.5, Tut: 0.5)

Number and data representation. Logical structure of computers. Instruction set architecture. Instruction execution sequencing. Assembly-language programming. Input/output interfaces and programming. Processor datapath and control unit design. Semiconductor memory technology and memory hierarchy design.
(Lec: 3, Lab: 0.5, Tut: 0.5)

Fundamentals of Data Structures and Algorithms: arrays, linked lists, stacks, queues, deques, asymptotic notation, hash and scatter tables, recursion, trees and search trees, heaps and priority queues, sorting, and graphs. Advanced programming in the C language. Introduction to object oriented programming concepts in the context of data structures.
(Lec: 3, Lab: 0.5, Tut: 0.5)

Introduction to object-oriented design, architecture, and programming. Use of packages, class libraries, and interfaces. Encapsulation and representational abstraction. Inheritance. Polymorphic programming. Exception handling. Iterators. Introduction to a class design notation. Applications in various areas.
(Lec: 3, Lab: 1, Tut: 0)

A study of the fundamental aspects of electromagnetic fields. The following topics are covered: the Maxwell's equations and the 3-dimensional wave equation for transmission lines; vector analysis, including orthogonal coordinate systems, and the calculus of field quantities; electrostatic fields including the concepts of electric potential, capacitance, and current and current density; magnetostatic fields including inductance; time-varying fields and the complete form of Maxwell's equations; basic transmission line phenomena including steady-state sinusoidal behaviour and standing waves, transient performance and impedance matching.
(Lec: 3, Lab: 0.25, Tut: 0.5)

This course encompasses team-based design to solve complex open-ended problems. Instruction is provided on problem definition, creation of ideas, and decision making that considers technical, economic, societal, and environmental factors. Attention is given to safety considerations, technical codes and regulations, and engineering ethics. Effective skills for oral and written communication are also emphasized. These aspects are applied in design project activity related to electrical and computer engineering.
K5 (Lec: Yes, Lab: Yes, Tut: Yes)

Fundamentals of data science: data capture, organization and maintenance, processing, and visualization. Implementation of data processing methods using Python. Application of the methods to design and implement a solution to a project-based data science problem.
K3 (Lec: Yes, Lab: Yes, Tut: No)

A team design project based around an autonomous, programmable, robotic vehicle. Students explore different sensors and software strategies for vehicle control and navigation, in addition to wiring up sensor and motor circuits. The design goal is to configure and program a vehicle to accomplish a specified task. A final project report that documents the experimentation, design, and testing must be produced.
COURSE DELETED 2023-2024
K1.5(Lec: No, Lab: Yes, Tut: No)

This is an introductory course on the design of analog electronic and digital logic circuits, using commonly available devices and integrated circuits. The properties of linear circuits, with particular reference to the applications of feedback, are discussed; operational amplifiers are introduced as the fundamental building block for the design of linear filters and amplifiers. Fundamentals of digital circuits including Boolean algebra, logic gates, combinational logic, sequential logic concepts and implementation are presented. Data acquisition and conversion is introduced, and the issues of noise and electromagnetic compatibility are discussed. Laboratory work is linked with lectures and provides practical experience of the subjects covered in lectures.
COURSE DELETED 2018-2019
(Lec: 3, Lab: 1, Tut: 0.5)

This is a first course on the basic concepts and applications of signals and systems analysis. Continuous time signals and systems are emphasized. Topics include: representations of continuous-time signals; linear time invariant systems; convolution, impulse response, step response; review of Laplace transforms with applications to circuit and system analysis; transfer function; frequency response and Bode plots; filtering concepts; Fourier series and Fourier transforms; signal spectra; AM modulation and demodulation; introduction to angle modulation.
COURSE DELETED 2019-2020
(Lec: 3, Lab: 0.25, Tut: 0.5)

This second course on signals and systems studies basic concepts and techniques for analysis and modeling of discrete-time signals and systems. The topics of this course are: sampling, reconstruction, and digitization; representations and properties of discrete-time signals and systems; linear time-invariant (LTI) systems; difference equations; discrete Fourier series; discrete-time Fourier transform; discrete Fourier transform; z-transform; analysis of LTI systems; filtering and spectral analysis. Computational realizations of the analysis tools and their applications are explored in the laboratory.
(Lec: 3, Lab: 0.5, Tut: 0.5)

This course provides an introduction to probabilistic models and methods for addressing uncertainty and variability in engineering applications. Topics include sample spaces and events, axioms of probability, conditional probability, independence, discrete and continuous random variables, probability density and cumulative distribution functions, functions of random variables, and random processes.
(Lec: 3, Lab: 0, Tut: 0.5)

An introduction to the basic principles, operating characteristics, and design of electric machines. Topics to be studied include: three-phase circuits; magnetic circuits; transformers; steady state behaviours of dc generators and motors; rotating magnetic fields; steady state operation of induction machines and synchronous machines; introduction to fractional horsepower machines; speed control of electric motors.
(Lec: 3, Lab: 0.75, Tut: 0.5)

This course provides an introduction to sensing and actuation in mechatronic systems. The topics include physical principles for the measurement and sensing of displacement, motion, force, torque, pressure, flow, humidity, radiation (visible and IR) and temperature using analog and digital transducers; actuating principles using continuous drive actuators, stepper motors, optical encoders and servo motors; and methods for signal collection, conditioning and analysis.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0.75, Tut: 0)

This course introduces sensor fabrication technologies. The topics include various types of sensors' design, fabrication processes, and applications. Students will learn standard micro and nano fabrication and cleanroom processing such as lithography, material deposition methods and systems, wet and dry etching, encapsulation, characterization methods and systems, etc. The effect of design parameters and fabrication processes on the performance of sensors will be discussed. The lab component of the course includes demonstration of the fabrication process in the cleanroom and operation of some sensors.
(Lec: 3, Lab: 0.25; Tut: 0)

Transistor-level modeling and design of analog and digital electronic circuits. Differential amplifiers, Gilbert Cell multipliers, multi-stage amplifiers, amplifier frequency response, negative feedback amplifiers, LC-tank and crystal oscillators, two-port networks. Advanced concepts in logic design. Students learn the basics of computer aided design (CAD) of integrated circuits including schematic simulation, layout, design rules, layout versus schematic verification and extracted circuit simulation. Laboratory work is design-oriented and students are introduced to advanced test and measurement techniques using vector network analyzers.
(Lec: 3, Lab: 0.75, Tut: 0.5)

Microprocessor bus organization and memory interfaces; parallel input/output interface design; assembly-language and high-level-language programming; interrupts and exceptions; timers; embedded systems organization and design considerations; integration in microcontrollers and programmable logic chips; interfacing with sensors and actuators; embedded system case studies.
(Lec: 3, Lab: 0.5, Tut: 0.5)

Number representation in digital computers, error analysis, and iterative calculations. Methods for finding roots of equations, solving systems of linear algebraic equations, single- and multi-variable optimization, least-squares analysis, curve fitting, differentiation and integration, and solving ordinary differential equations. Implementation of numerical algorithms in software.
(Lec: 3, Lab: 0.5, Tut: 0)

Network architecture with physical, data link, network, and transport layers for frame transmission and packet switching, standards such as Ethernet and 802.11 for wired and wireless networks, protocols such as TCP/IP, internetworking, routing, and socket programming.
(Lec: 3, Lab: 0, Tut: 0.5)

High-performance logic design for arithmetic circuits; memory system designs based on static and dynamic RAMs; computer bus protocols and standard I/O interfaces; mass storage devices; hardware description languages (VHDL, Verilog); fault testing, design for testability, built-in self-test, memory testing, and boundary-scan architectures; asynchronous sequential circuit design; introduction to GPU architectures and GPU computing. The course is supplemented by a CPU design project that allows students to become proficient with Field Programmable Gate Array (FPGA) devices and associated CAD tools, as well as with GPU computing through nVidia CUDA or OpenCL languages.
(Lec: 3, Lab: 1, Tut: 0.25)

Methodology for object-oriented software design and implementation, modeling notations/languages, template libraries, considerations for graphical user interfaces, techniques and tools for managing software projects in teams, and documentation for requirements analysis and system design.
(Lec: 3, Tut: 0.5, Lab: 0)

Operating systems for conventional shared memory computers. System services and system calls, concurrent processes and scheduling, synchronization and communication, deadlock. File systems and protection, memory management and virtual memory, device management and drivers. Unix operating system. Real-time and distributed systems. Security.
(Lec: 3, Lab: 1, Tut: 0)

Algorithm design and analysis; techniques based on divide and conquer, branch and bound, dynamic programming, and the greedy approach; computer engineering applications such as circuit partitioning and logic circuit technology mapping; computational complexity and NP-completeness.
(Lec: 3, Lab: 0.5, Tut: 0.5)

Partial differential equation solutions to Maxwell's Equations; Introduction to the Smith chart; uniform plane waves; reflection of plane waves; normal and oblique incidence; analysis and applications of rectangular waveguides; resonant cavities; optical fibres; introduction to antennas; aperture antennas.
(Lec: 3, Lab: 0.25, Tut: 0.5)

The goal of this course is to prepare students for definition, design, management, and development of engineering projects and products. Students will learn about problem definition and impact analysis from an economic standpoint as well as other perspectives. Different design principles, management techniques, and development methodologies will be described. Culture and communication in teams will be discussed, followed by important concepts in ethics and intellectual property. Specific software and tools that are available for facilitating design/development activity will be introduced and utilized throughout the term. Students will apply concepts and explore issues through projects and laboratory activity.
K3.5(Lec: Yes, Lab: Yes, Tut: Yes)

This is an introductory course in biomedical signal and image processing.
Topics include: biopotential generation and detection; the biomedical signals
with a focus on the electrocardiogram and electroencephalogram; recording artifacts and signal compression; major medical imaging modalities; 2D and 3D image formation; image processing techniques including spatial and
frequency-domain filtering, feature extraction and convolutional neural networks; applications in diagnostics, therapeutics, and interventions.
(Lec: 3, Lab: 0, Tut: 0)

The course surveys: microarray data analysis methods; pattern discovery, clustering and classification methods; applications to prediction of clinical outcome and treatment response; coding region detection and protein family prediction. At the end of this course, students should be able to appreciate some approaches related to individualizing medical treatment, as well as to apply some of the methods, such as alternatives to PCA, to more traditional engineering problems.
(Lec: 3, Lab: 0, Tut: 0)

Sampling theorem, filter realization structures, quantization errors and finite word length effects, digital signal processor programming, finite and infinite impulse response filter design techniques, discrete and fast Fourier transform.
(Lec: 3, Lab: 0.5, Tut: 0.5)

Recent DSP topics including: bandpass sampling, oversampling A/D conversion, quantization noise modelling, multi-rate signal processing, filterbanks, quadrature mirror filters, applications to communications systems, speech and image compression; processing of discrete-time random signals.
NOT OFFERED 2022-2023
(Lec: 3, Lab: 0.5, Tut: 0)

Supervised and unsupervised machine learning methods for regression, classification, clustering, and time series modeling. Methods of fitting models. The problem of overfitting and techniques for addressing it. Deep learning and neural network models. Processes for how to refine/ implement/ test applications of machine/deep learning algorithms.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0.25, Tut: 0.25)

This course introduces the basic concepts of power electronics, which include power semiconductor devices and switching power converters. Emphasis is placed on the analysis and design of various power electronics circuits. Their industrial application, such as in telecommunications and computing, will also be discussed. More specifically, the course will cover the characteristics of switching devices, especially that of MOSFET. The course will also cover the operation of various switching converters such as phase controlled ACto- DC converters, AC voltage controllers, DC-to-DC switching converters, DC-to-AC inverters and switching power supplies. The requirements and configurations of power systems for telecommunications will be introduced. The techniques to analyze and design these power systems using available components will also be discussed. Computer simulation will be used to analyze the detailed operation of switching converters.
(Lec: 3, Lab: 0.25, Tut: 0)

Energy resources and electric power generation with particular emphasis on renewable energy systems such as solar, wind, and biomass; review of balanced and unbalanced 3-phase systems; review of per-unit systems; real and reactive power, sequence networks and unsymmetrical analysis; transmission line parameters; basic system models; steady state performance; network calculations; power flow solutions; symmetrical components; fault studies; short circuit analysis; economic dispatch; introduction to power system stability, operating strategies and control; modern power systems and power converters; DC/AC and AC/DC conversion; and introduction to DC transmission.
(Lec: 3, Lab: 0, Tut: 0.5)

Review of basic electric machines. Salient pole synchronous machines. Transient and dynamic behaviour of electric machines. Characteristics and applications of special motors such as servo motors, stepper motors, PMmotors, brushless dc motors, switched reluctance motors and linear motors. Solid state speed and torque control of motors.
(Lec: 3, Lab: 0, Tut: 0)

Introduction to linear systems and feedback control. Topics include introduction to automatic control, overview of Laplace transformation, linear models of dynamic systems, time-domain specifications of first and second order systems, stability analysis using Routh-Hurwitz criterion, steady-state error and disturbance rejection, PID control, stability analysis and linear controller design using root locus method, Nyquist criterion, and Bode plots, and introduction to state-space analysis. These methods are applied and tested using software such as MATLAB/Simulink, and laboratory experiments.
(Lec: 3, Lab: 0.5, Tut: 0.5)

This course provides an introduction to modeling and analysis of the dynamics of mechatronic processes and computer control of such systems. Topics include modeling and simulation of mechanical, electrical, thermal, and fluid systems, sampled-data systems and equivalent discrete system, overview of
Z-transform, dynamic response of second-order discrete systems,
stability analysis and design of linear discrete-time control systems
using root locus and frequency response methods. The modeling
and controller design methods are implemented and tested using MATLAB/Simulink and laboratory experiments.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0.25, Tut: 0)

Robotics is an interdisciplinary subject concerning areas of mechanics, electronics, information theory, control systems and automation. This course provides an introduction to robotics and covers fundamental aspects of modeling and control of robot manipulators. Topics include history and application of robotics in industry, rigid body kinematics, manipulator forward, inverse and differential kinematics, workspace, singularity, redundancy, manipulator dynamics, trajectory generation, actuators, sensors, and manipulator position and contact force control strategies. Applications studied using MATLAB/Simulink software simulation and laboratory experiments.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0.5, Tut: 0)

Review of MOS transistor structure and operation; overview of wafer processing and device implementation, layout and design rules. CMOS gate design; static
and dynamic logic; modelling of transients and delays. Clocked circuits; interconnect effects, and I/O. Memory and programmable logic arrays.
Technology scaling effects; design styles and flow.
(Lec: 3, Lab: 0.25, Tut: 0)

Topics include; an introduction to noise and distortion in electronic circuits, analysis and design of biasing circuits, references, ADCs and DACs, power amps, mixers, modulators and PLLs along with a short introduction to analog filter design.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0, Tut: 0.25)

In the first part of this course modern microelectronic circuits are covered and in the second part these circuits are used in new and emerging applications. Topics include: active and passive filtering circuits, phase locked loops, frequency synthesizers, RF modulators, clock and data recovery circuits, RF energy harvesting, ultra low-power circuits, biotelemetry systems, biological sensors, neurostimulator circuits, introduction to radiometry and radar imaging.
(Lec: 3, Lab: 0.5, Tut: 0)

Representation of signals and noise, Gaussian processes, correlation functions and power spectra. Linear systems and random processes. Performance analysis and design of coherent and noncoherent communication systems, phase-shift-keying, frequency-shift,-keying, and M-ary communication systems. Optimum receivers and signal space concepts. Information and its measure, source encoding, channel capacity and error correcting coding.
(Lec: 3, Lab: 0, Tut: 0.5)

Fundamental principles and practice of current wireless communications systems and technologies. Historical context, the wireless channel including path loss, shadowing, fading, and system modes in use. Capacity limitations on transmission rate, transmission of data by signaling over wireless channels via digital modulation, optimum receivers, countermeasures to fading and interference via diversity and equalization, multiple user systems including multiple access FDMA, TDMA, CDMA, FDMA/TDMA, uplink and downlink; capacity and power control, design of cellular networks. Selected standards and emerging trends are also surveyed.
(Lec: 3, Lab: 0, Tut: 0)

This course covers advanced topics in computer architecture with a quantitative perspective. Topics include: instruction set design; memory hierarchy design; instruction-level parallelism (ILP), pipelining, superscalar processors, hardware multithreading; thread-level parallelism (TLP), multiprocessors, cache coherency; clusters; introduction to shared-memory and message-passing parallel programming; data-level parallelism (DLP), GPU architectures.
(Lec: 3, Lab: 0, Tut: 0.5)

Fundamental concepts and applications of intelligent and interactive system design and implementation. Topics include: problem formulation and experiment design, search techniques and complexity, decision making and reasoning, data acquisition, data pre-processing (de-noising, missing data, source separation, feature extraction, feature selection, dimensionality reduction), supervised learning, unsupervised learning, and swarm intelligence.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0.5, Tut: 0)

Cryptography topics include: block ciphers, advanced encryption standard, public key encryption, hash functions, message authentication codes, digital signatures, key management and distribution, and public-key infrastructure. Network security topics include: user authentication, network access control, Kerberos protocol, transport layer security (TLS), IP security (IPSec), electronic mail security, and wireless network security.
(Lec: 3, Lab: 0, Tut: 0)

Image acquisition and representation, histogramming, spatial- and frequency-domain filtering, edge detection, motion segmentation, color indexing, blob detection, interest operators, feature extraction, camera models and calibration, epipolar geometry and stereovision. The lab and assignments will emphasize practical examples of machine vision techniques to industrial and mechatronic applications.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0, Tut: 0.5)

Deep learning methods are highly effective at solving many problems in computer vision. This course serves as an introduction to these two areas and covers both the theoretical and practical aspects required to build effective deep learning-based computer vision applications. Topics include classification, convolutional neural networks, object detection, encoder-decoders, segmentation, keypoint and pose estimation, generative adversarial networks, and transformers. Labs and assignments will emphasize practical implementations of deep learning systems applied to computer vision problems.
(Lec: 3, Tut: 0, Lab: 0.5)

Client/server architectures, multicasting, real-time distributed protocols, naming and name services, fault tolerance, security, and embedded-systems considerations.
(Lec: 3, Lab: 0, Tut: 0)

Overview of light-matter interaction, design of optical waveguides, modeling of photonic devices, light propagation in periodic and subwavelength structures. Applications of photonics in LIDAR for autonomous vehicles, design of optical phased array, design of holography, medical imaging and sensing, optoelectronics and renewable energy.
(Lec: 3, Lab: 0, Tut: 0)

This course introduces the analysis and design of microwave components and systems. Topics include: modeling of high frequency circuits; transmission lines; scattering parameters; impedance matching; passive microwave components; amplifiers, mixers and oscillators; noise in receivers; elemental antennas and simple and phased arrays; communication links - microwave land, cellular and satellite systems; performance and link budget analysis. The laboratory work is design oriented and implements the lecture material.
NOT OFFERED 2023-2024
(Lec: 3, Lab: 0.75, Tut: 0.5)

This course introduces fundamental principles and applications of fiber optic communication systems. Topics include Fabry-Perot and distributed feedback semiconductor lasers, planar dielectric waveguides, propagation characteristics of single-mode optical fibers, p-i-n and avalanche photodiodes, and digital receiver performance. Device technology and system design applications are considered.
(Lec: 3, Lab: 0.25, Tut: 0.5)

Students work in groups of three on the design and implementation of electrical engineering projects, with the advice of faculty members. This course is intended to give students an opportunity to practice independent design and analysis. Each group is required to prepare an initial engineering proposal, regular progress reports, and a final report together with a formal seminar on the project and its results.
K7(Lec: Yes, Lab: Yes, Tut: Yes)

Students will be assigned individual Research Topics. Students must work under the supervision of a faculty member. Grade will be based on the progress in arriving at a solution to the assigned problem.
COURSE DELETED 2021-2022
(Lec: 0, Lab: 6, Tut: 0)

The students continue working on their assigned problems in ELEC 491 under the supervision of the same faculty member. Upon completion of their thesis, students must give oral and written presentations. Grades will be based on the quality of the analysis of the problem, the proposed solution, and written and oral presentations. Demonstration of effective written and oral communications skills is required.
COURSE DELETED 2021-2022
(Lec: 0, Lab: 6, Tut: 0)

The student works on a research project under the supervision of a faculty member. A research problem is formulated and the problem is contextualized within the discipline. The student does a current literature review, and explores in detail a solution to the research problem. Subject to Department approval.
K3.5(Lec: No, Lab: No, Tut: No)

Students work in groups of three on the design and implementation of computer engineering projects, with the advice of faculty members. This course is intended to give students an opportunity to practice independent design and analysis. Each group is required to prepare an initial engineering proposal, regular progress reports, and a final report together with a formal seminar on the project and its results.
K7(Lec: Yes, Lab: Yes, Tut: Yes)