90 graduate courses in Waterloo’s course catalog for Spring 2021, from UW Open Data. uwloo can’t read that term’s Graduate Calendar, so this stands in for it; the calendar itself is in Waterloo’s archive.
This biomedical engineering core course focuses on equipping students with the foundational knowledge in human biology through a problem-solving oriented treatment of biological phenomena at both physiological and cellular levels. The major aim of this course is to develop students' literacy in biology and to show them how various biological phenomena can be analytically explained and justified with numbers. It is also intended to illustrate how biology knowledge can be integrated with engineering principles to address real-world diagnostic needs. Case descriptions would be included of medical devices that involved discipline-specific knowledge in electrical and computer engineering.
Fundamental optimization techniques. Modelling. Shortest path. Network flow. Matching. Set packing, covering partitioning. Branch and bound. Cutting Planes, Dynamic programming. Search Heuristics. (Students will gain valuable background in optimization techniques that are applicable to a wide range of engineering problems. They will also gain experience using a state of the art optimizer, in solving an optimization problem of their own choice using techniques discussed in the course).
Optimum mininum mean-square error (MMSE) Wiener filtering. Parametric and non-parametric spectrum estimation. Eigenstructure-based frequency estimation. Statistical parameter estimation using maximum likelihood (ML), maximum a posteriori probability (MAP), minimum mean-square error (MMSE) and least squares (LS) methods. Adaptive signal processing using least-mean-squares (LMS) and recursive least-squares (RLS) approaches. Discrete-time Kalman filtering. Recommended background: ECE 316: Probability Theory/ECE 342: Signals and Systems/ECE 413: Digital Signal Processing/ECE 604: Stochastic Processes.
Theory of random variables, vectors and processes. Conditional probabilities and expectations. Convergence of sequences of random variables. Markov chains in discrete and continuous time. Poisson processes. Basic renewal processes. Stationary random processes, correlation, and power spectra. Emphasis on problem solving using probabilistic approaches.
Introduction to queueing theory, queueing models, performance measures, performance analysis and evaluations, Poisson arrivals and exponential service times, Little's formula, Markov and semi-Markov processes, birth-death processes, single server and multiserver queues, single stage and tandem networks, open and closed networks.
This is an introductory course on algorithms at the graduate level. It assumes familiarity with basic data structures such as lists, queues, trees and graphs, and emphasizes creativity in the design of algorithms, and rigorous analysis. Correctness (soundness and completeness) and efficiency (with respect to average-, best- and worst-case time and space) properties are considered in the context of algorithms for classes of problems such as optimization and decision problems. The course also gives insights into when a problem may be intractable, and how we may deal with intractability.
This course gives an in-depth coverage of technical concepts that are fundamental to the use of ultrasound in biomedicine. Concepts to be addressed include: acoustic wave propagation theory, field profile in ultrasound imaging, principles of ultrasound-based flow estimation, and the biophysical foundations of therapeutic ultrasound. The overall aim of this course is to equip students with essential foundational knowledge in biomedical ultrasonics, starting from first principles in wave physics.
ECE 608Quantitative Methods in Biomedical Engineering
This biomedical engineering core course focuses on topics related to the use of quantitative tools in biomedical engineering research studies. It will teach students how to conduct statistical analysis of biomedical data, design biomedical experiments that can offer statistical insight, and apply computational methods to solve problems in biomedical engineering. Educational emphasis will be placed on developing students' core competence in biostatistics and biomedical computing, so as to prepare them to pursue biomedical engineering investigations that are backed by quantitative reasoning and numerical insights.
This course introduces a quantitative understanding of cell biology at the molecular level. Guided with real experimental data, biological processes and systems are modeled using fundamental physical principles and engineering analytic techniques, including free-energy minimization, statistical mechanics, random walk models, electrostatics, diffusive dynamics, electrochemical equilibrium, complex networks, feedback system analysis, Turing reaction-diffusion equations, and sequence analysis. Various complicated biological phenomena will be shown to be explicable with the same simple underlying principles.
This course is concerned with the fundamentals of broadband communication networks including network architecture, Switch fabrics, design methodology; traffic management, connection admission control (CAC), usage parameter control (UPC), flow and congestion control; capacity and buffer allocation, service scheduling, performance measures, performance modeling and queueing analysis.
Representation of bandpass signals and systems, modulation and demodulation for the additive white Gaussian noise channel, optimal demodulation for signals with random phase, noncoherent detection for binary and M-ary orthogonal signals, hard and soft decision decoding for linear codes, concatenated codes, performance of coded modulation systems, characterization of fading multipath channels, diversity techniques, performance of coded systems on fading channels, direct sequence and frequency hopped spread spectrum systems.
An introduction to information measures, entropy, mutual information and information divergence, noiseless codes and the noiseless coding theorem, channel capacity for discrete and continuous channels, randomly chosen code words, the noisy coding theorem, error rate exponents, computational cut-off rate and its application to digital communications.
This course covers the fundamental concepts and methods, as well as state-of-the-art theories and technologies in the field of image processing and visual communications. Topics include fundamental digital image and video processing methods; image analysis and understanding; statistical image modeling and perception; and robustness, scalability and security issues in visual communications.
ECE 614Communications Over Fading Dispersive Channels
Overview of mobile communications, characterization and modeling of wireless fading dispersive channels, optimum receiver structure, transmission performance in fading channels, diversity and performance improvement, co-channel interference, spread spectrum and multiple access, capacity analysis in cellular environments.
ECE 617Data Compression with Applications to Speech and Image Coding
This course consists of three parts: Part 1 will be concerned with the definitions of entropies as information measures and the derivation of the rate distortion function of Gaussian sources, which will form the basis for performance comparison. Part 2 will discuss the derivations, design and performance of certain compression techniques, including dpcm/entropy coding, predictive coding, linear predictive coding (LPC), adaptive predictive coding (APC), vector quantization, and tree and trellis coding. Part 3 will consider applications of compression techniques to speech and image processing.
Organization of high performance digital computers, high speed arithmetic algorithms, control unit and data flow organization. Pipeline systems. Stack machines, associative processors, parallel processors. Performance evaluation.
Syntax, semantics, and usage of the VHDL hardware description language. Modeling concurrency in VHDL, in other hardware description languages, and using other simulation techniques. Modeling, design, and implementation at the register-transfer level. Functional verification techniques. Timing analysis. Introduction to power analysis and optimization. Introduction to faults and testing.
Evolution of computer security. Types of security threats, hardware threats, software threats, physical threats, cryptanalysis. The theory of secure message passing. Methods of encryption, private networks, Data Encryption Standard, Public Key Cryptosystems. Secrecy and Privacy in a network environment, long haul networks, local area networks. Protocols for computer network security.
ECE 630Physics and Models of Semiconductor Devices
Basics of semiconductor physics. Physical principles and operation of p-n junctions, metal/semidconductor contacts, MOS capacitors, MOS field-effect transistors, and related optoelectronic devices. Short-channel MOSFETs, modern MOSFETs, and future transistor technologies. Introduction to device simulators and SPICE models.
Physical source of solar radiation; direct & diffuse radiations; review of electronic materials; semiconductor concepts; optical absorption; generation and recombination processes in semiconductors; operating principles of photovoltaic devices; homo- and hetero- junction devices; equivalent circuits; quantum efficiency; current-voltage characteristics; Efficiency limits in photovoltaic devices; short circuit current and open circuit voltage losses; temperature effect; material-imposed limits; theoretical and practical limits; Photovoltaic device design and fabrication; silicon-based devices; gallium arsenide devices; thin film devices; device simulation; fabrication technologies; Advanced photovoltaic concepts; nano-structure and organic PV devices; System-level photovoltaics; module structure and design; back-end electronics; stand-alone and grid-interactive systems; photovoltaic hybrid systems.
This course will cover the following topics; Basics of quantum mechanics; Quantum confinement; Boundary conditions; Schrodinger equation; Basic function; Density matrix; Energy bands; Subbands; Reciprocal lattice; Brillouin zone; Graphene and graphene nanoribbon; Transport in nanoelectronic devices.
The course gives an overview of organic electronic and optoelectronic devices. It begins with a review of electronic structure of single organic molecules as a guide to the electronic behaviour of organic aggregates.Various relevant material phenomena are reviewed; including topics from photophysics (absorption and emission of light, excited states, radiative and non-radiative transitions), intermolecular charge transport mechanisms (hopping, disorder), charge injection and transport models, and energy transfer processes. Their applications in light emitting devices, solar cells, thin film transistors, photodetector and imaging photoreceptors, etc. are discussed. Aspects related to device fabrication and patterning may also be addressed.
ECE 635Fabrication in the Nanoscale: Principles, Technology, & Applications
The research in nanoscale science and technology has seen a very fast growth in the past years. The cornerstone for this exciting growth is the ability to create nanoscale patterns, which is the object of the current course. The course will cover all major nano-lithography technologies capable of generating or duplicating sub-lOOnm patterns, including lithographies based on photons, charged beams, scanning probes, replication and self-assembly. Within each lithographic technique, the students will learn its working principle, related materials and instrument, process and limit. This course is complementary to ECE 631 (Microelectronic Processing Technology), but takes fabrication and associated theory into nanoscale.
Design of MOS and bipolar analog integrated circuits at the transistor level, with an emphasis on the design of single-stage and multi-stage op amps. Related topics include biasing, compensation and noise will be covered. In addition, higher level analog and mixed analog/digital subsystems will be discussed, time permitting. Students enrolling in this course are expected to have a background equivalent to the material covered in ECE 242, formerly ECE 332.
Design of CMOS digital integrated circuits at the transistor level. Related topics include MOSFET switch and 1-V models, logic gate design, transistor sizing, interconnect parasitics, gate delay, timing design, logical effort, static and dynamic logic families, arithmetic structures, latch and flip-flop elements, memory cells and arrays, and input/output circuitry. Students enrolling in this course are expected to have a background equivalent to the material covered in ECE 242, formerly ECE 332.
Overview of basic physical processes in semiconductors and their interactions with thermal, radiant, mechanical, or chemical input signals. Review of microtransducer materials and technologies. Principles and operation of integrated thermal sensors (thermistors, thermopiles, active IC elements, pyroelectric devices), radiant sensors (optoelectronic, infrared and radiation sensors), magnetic sensors (Hall devices, magnetoresistors, magnetotransistors), (mu)mechanical sensors (piesoelectric and peizoresistive devices, flow sensors and resonant structures), chemical sensors (ion, gas and humidity sensors, CHEMFETs, biosensors, SAW devices), and micro-actuators ((mu)valves, (mu)pumps, (mu)motors). Overview or pertinent interface and modelling techniques.
ECE 639Characteristics & Applications of Amorphous Silicon
Growth and structure of amorphous silicon (morphology, growth mechanisms, silicon bonding structure, continuous random network, hydrogenation). Electronic states in amorphous silicon (density of states, band tails, optical transitions, defects and defect states). Doping of amorphous silicon, defect reactions and metastable effects. Electronic transport and recombination in amorphous semiconductors. Using amorphous silicon in practice (contacts and surfaces). Applications of amorphous silicon (Schottky diodes, solar cells, optical and radiation sensors, thin film transistors, flat panel displays, large-area electronics).
Transistor-level design of circuits for wideband RF front-ends. An overview of 2G (GSM) and 3G (W-CDMA) standards and relevant radio architectures is presented, with key system specifications mapped onto circuit specifications. On-chip passive component design and simulation aimed at maximizing RF performance is discussed in detail. Circuit examples include: wideband preamplifiers and gain blocks, I-Q up/downconverters, voltage- and digitally-controlled oscillators (VCO/DCO), and power amplifier drivers. Design of circuit blocks for mm-wave frequency applications and RF testing, packaging and characterization are also discussed. Understanding of analog circuit design and semiconductor devices, and analog circuit simulation experience (e.g., SPICE) is required.
Formulation of equations for arbitrary circuits, active network analysis; sensitivity calculations in the frequency domain; simple integration methods for time domain solution; numerical laplace inversion for transient solution of linear lumped and distributed networks; solution of nonlinear circuits; detailed time domain solution of nonlinear networks; simulation of switched networks in time domain; introduction to switched capacitor networks; iterative simulation methods.
ECE 647Algorithms for Physical Design of Digital Integrated Circuits
An introduction to the problems and algorithms that arise during the Computer-Aided Design (CAD) of digital circuits. Course emphasis is on the backend of the CAD flow such as algorithms for solving problems including: technology mapping, partitioning, floor-planning, clustering, placement, routing and physical synthesis.
ECE 649Nanoelectronic Circuits and Systems Project
This is a project course, designed exclusively for MEng students completing the Nanoelectronic Circuits and Systems specialization. Students will carry out a research project over one academic term, under the direct supervision of an ECE faculty member from the associated research area. At the end of the term, a written Project Report has to be submitted, which will be evaluated and marked by the Supervisor.
Software Systems - Systems programming and operating systems, scripting, system calls, libraries, compilers and interpreters. Mathematical logic - propositional & predicate logic, and some higher-order logics, syntax, semantics, entailment, deduction, use of logic in software. Data structures - lists, stacks, queues, heaps, trees, graphs, and algorithms to manipulate such data structures. Graduate students who have previously taken ECE 750 with the topic title Methods and Tools for Software Engineering are not eligible to take ECE 650.
Fundamentals of software requirement analysis, software development as an engineering activity, basic process models, software specifications, modularity, cohesion, coupling, encapsulation, information hiding, principles of object oriented design, software project management, quality assurance and control. Priniciples of Software Architecture: Fundamental software architecture styles, synchronous & as synchronous communication of software components. Languages for software design specification: UML (class diagrams, sequence diagrams, collaboration diagrams, state diagrams). Overview of verification and validation techniques. Maintenance, evolution and reengineering, configuration management. Software metrics, quality assurance, fundamental cost and effort prediction models. Trends in software engineering (e.g., model-driven development, agile approaches).
ECE 652Methods and Principles of Safety-critical Embedded Software
The application of formal test methods based on the structural and behavioural properties of software systems at the unit integration, and system testing levels; for conventional and object-oriented implementations. Related Background: Prior knowledge of a programming language and a certain maturity in compilers, operating systems, abstract data structures, object-oriented and programming skills.
ECE 653Software Testing, Quality Assurance and Maintenance
Introduces students to systematic testing of software systems. Software verification, reviews, metrics, quality assurance, and prediction of software reliability and availability. Students are expected to have programming experience with reading and writing code for large projects.
The course consists of two related parts. The first part deals with the engineering of reliable software. It introductes basic software reliability concepts, descritbes relevant models and discusses processes for engineering of reliable software, including schemes and patterns for the design of reliable and fault tolerant software. The second part addresses development of secure software. It presents key software security concept, techniques and models, overviews major software security vulnerabilities and their exploitation, and considers processes for development of secure software.
Prereq/coreq: ECE 650 or 750 Tpc 26 or instructor consent. Antireq: ECE 750 Topic 2
ECE 655Protocols, Software and Issues in Mobile Systems
This course is concerned with the architecture, protocol and software aspects of mobile systems. The topics to be discussed include mobile communication and computing systems, supporting ad hoc networks, mobile network and transport layers, wireless application protocol, support for mobility, service advertisement and discovery in mobile systems, and emerging issues such as enviornment-aware software and low-power protocols and software.
This course covers data models, file systems, database system architectures, query languages, integrity and security and database design. Students attending this course should have at least a 4A level Electrical Engineering or Computer Engineering background.
Prereq/coreq: ECE 650 or 750 Tpc 26 or instructor consent.. Antireq: ECE 750 Topic 18
Conventional approaches for tackling complex systems are usually implemented under the assumption of a good understanding of the process dynamics/functionalities and its operating environment. These techniques fail, however, to provide satisfactory results when applied to ill-defined processes (for which analytical and experimental modeling may not be easily obtained) that may operate in unpredictable and possibly noisy environment. Recent developments in the area of intelligent systems and soft computing have presented powerful alternatives for dealing with the behavior of this class of systems. This course outlines fundamentals of soft computing based design approaches using such tools as approximate reasoning, fuzzy inferencing, neural networks, evolutionary algorithms, and neuro-fuzzy systems. Fundamentals and advances on these procedures are outlined along with their potential applications to various real world applications in virtually most fields of engineering including pattern recognition, system planning, classification, power generation, intelligent transportation, systems and control, intelligent mechatronics, optimization, communication, robotics and manufacturing, to name a few.
Prereq: ECE 650 or 750 Tpc 26 or instructor consent. Coreq:ECE 650 or 750 Tpc 26 or instructor consent. Antireq: ECE 750 Topic 16
Engineers encounter data in many of their tasks. Whether the sources of this data may be experiments, databases, computer files, or the Internet, there is a dire need for effective methods to model and analyze the data and extract useful knowledge and information from it. This course aims to provide engineering graduate students with essential knowledge of data representation, grouping, mining and knowledge discovery.
Building large-scale and complex software systems from available parts with the goal of increasing return on investment, decreasing time to market, and assuring quality and reliability. The course covers the basic software component concepts, overview of advanced topics on software components and component-based software engineering from research and practice.
This course is concerned with recent developments in intelligent sensors and wireless sensor networks. This course will introduce students to diverse fundamental issues encountered in designing and analyzing intelligent sensors and sensor networks (mobile and stationary), with emphasis on mission critical applications.
Application of state-of-the-art high power electronics to power transmission and distribution systems. The emphasis will be on three important application areas - high voltage direct current (HVDC) transmission systems, flexible AC transmission Systems (FACTS) and Custom Power devices. The course addresses FACTS controllers including: static synchronous compensators (STATCOM), static synchronous series compensators (SSSC), interphase power flow controllers (IPFC) and unified spower flow controllers (UPFC). Custom power devices such as shunt DSTATCOM, series compensating DVR and unified power quality conditioners (UPQC) are also discussed. This course will concentrate on the operating principles, models, and control and performance of power electronic systems used in these applications. Background required - ECE 463 or equivalent.
The definitions and concepts associated with short circuit, power flow and stability analysis are presented and discussed. Models, techniques and tools used for these types of studies are discussed with a practical perspective, and applied to the comprehensive analysis of a typical test system. Controls and protections for voltage, angle and frequency control and regulation, such as Automatic Voltage Regulators (AVR), Power System Stabilizers (PSS) , Automatic Generation Control (AGC), under-voltage and under-frequency relays, are also studied and applied. [Note: Required background - ECE 467 or equivalent.}
This course is intended to embrace power electronic aspects together with the broader issues of the systems of energy processing for emerging technologies. Within this framework, topics include performance, selection and optimization of power semiconductor devices including thyristors, GTOs, triacs, BJTs, MOSFETs, IGBTs and MCTs; classification, circuits and performance of converting circuits including rectifiers, inverters, choppers and cycloconverters; control and protection of conversion circuits; requirements and constraints of energy processing systems such as variable speed drives, high energy battery installations, transportation, solar and wind generators and industrial processes.
The basic structure, functional characteristics and protection schemes of the main components that make up a power system are studied, in particular generators, transformers, transmission lines, cables, loads, HVDC and FACTS controllers. Models of these components for detailed electromagnetic transient analysis and phasor-based studies such as power flow and stability studies are discussed in detail, and various models are compared and validated through simulations performed with commercial software packages. Required Background - ECE 631 or equivalent.
This course deals with the new emerging technology in high voltage engineering. It is divided into five parts. The first part of the course in a review of the basic fundamentals of high voltage engineering. The second part deals with the new techniques in partial discharge measurements. The third part of the course deals with measurements of charge distribution in solid dielectric. The fourth part of the course discusses the optical fiber based monitoring techniques of the high voltage high power equipment. The last part of the course deals with the application of high voltage engineering in power systems.
The course deals in details of power system operation in the context of restructured electricity markets. Basics of power system operation - economic load dispatch, concept of marginal cost, Kuhn-Tucker's conditions of optimum, unit commitments, hydro-thermal coordination, optimal power flow analysis and security constrained economic dispatch are introduced. On the topic of transmission open access, the course discusses transmission pricing paradigms and the role of distribution factors in pricing. Transmission operations cover congestion management methods and firm transmission rights. Ancillary services procurement and pricing and power system security are discussed. Background - ECE 467 or equivalent.
This course covers topics related to sustainable and clean energy resources; distributed generation and utility interfacing. The following topics are covered: Wind power generators; construction; operation theory, modeling and analysis. Wind turbine interfacing techniques with the grid. Photovoltaic energy sources; construction, modeling, loading characteristics and interfacing requirements. Fuel cells; types, construction, modeling and characteristics, operation theory and interfacing requirement. Distributed generation concept; Barriers to DG interfacing; Reactive power control applications using the DG interfacing; Ancillary services supplied by DG. System protection requirements with DG.
This course covers the following topics in distribution engineering: Load Characteristics and distribution system load forecasting; Distribution system planning; Distribution system automation; Design and application of distribution transformers; Design and optimal operation of sub-transmission lines and distribution systems; Distribution system voltage regulation; Reactive power control for distribution systems; Application of capacitors to distribution systems; Calculation of voltage drops in lateral distribution systems; Calculation of power losses in distribution systems; Introduction to distribution system protection. Background Required - basic knowledge of power system operation and analysis.
Selected topics from theory of solid insulation breakdown. Conduction process in insulating liquids. Hydro dynamic processes. Theories of breakdown due to gaseous inclusion, moisture inclusion and particle contamination. Kinetic theory of gases. Breakdown mechanism in uniform electric fields. Corona and breakdown in non-uniform electric fields. Compressed gas insulation.
Fundamentals of microwave and RF circuit analysis, design and measurements; Generalized transmission line analysis; S-parameters; Coupler and filter design; Diode-detectors, and mixers; Low-noise and power amplifiers, oscillators; Computer aided design of RF circuits.
Overview of optical properties of semiconductors and elements of plane wave propagation, theory and design of light emitting diodes, laser diodes, and detectors, optical spectra and transitions, spontaneous and stimulated emission, population inversion, carrier and optical confinements in heterostructures, quantum-well lasers, optoelectronic detectors, bandgap engineered graded structures, staircase type or superlattice structures for detectors, detailed quantum efficiency calculations and detector noise considerations, Introduction to monolithic integrated circuits.
ECE 675Radiation & Propagation of Electromagnetic Fields
Mathematics of time varying electromagnetic fields, linear antennas self and mutual impedance, aperture antenna, wave diffraction theory, geometrical theory of diffraction (GTD).
This course introduces the fundamental concepts and the most recent achievements in physical realization of quantum information devices and systems in three platforms; Nuclear Magnetic Resonance (NMR), quantum photonics, and superconducting electric circuits.
The course is introductory and emphasizes the fundamental concepts and engineering applications without a previous exposure to quantum mechanics. Examples and problems are designed to address the applications of the course contents to real problems in electronic, optoelectronic, photonic and superconductive devices.
ECE 678Fourier Optics and Optical Signal Processing
Analysis of two-dimensional linear systems, Scalar diffraction theory, Fourier transforming properties of lenses, Frequency analysis of optical imaging systems, Spatial filtering and optical information processing, Synthetic Aperture Radar (SAR) - data processing, Wavefront-reconstruction.
An introduction to control theory for linear time-invariant finite-dimensional systems from both the state-space and input-output viewpoints. State-space theory: the concepts of controllability, observability, stabilizability, and detectability; the pole-assignment theorem; observers and dynamic compensation; LQR regulators. Input-output theory: the ring of polynomials and the field of rational functions; the algebra of polynomial and rational matrices; coprime factorization of transfer matrices; Youla parametrization, introduction to optimal control.
Estimation theory, linear and nonlinear regression, numerical techniques for parameter estimation for static and dynamic models, the Kalman filter and extensions, stochastic approximation, empirical dynamic models - especially for linear sampled data systems with stochastic inputs.
ECE 686Filtering and Control of Stochastic Linear Systems
This is a course on continuous-parameter state estimation and control for stochastic linear systems. It is based on a single unifying theme, namely that state estimation in linear systems is equivalent to projection onto a closed linear subspace generated by an observation process in a Hilbert space of random variables. This formulation of state estimation leads to the innovations theorem of Kailath, and this in turn has a number of corollaries of considerable practical importance, such as the Kalman-Bucy filtering formulae and the Rauch-Tung-Striebel prediction formulae which are much used for example in problems of inertial guidance and control in aerospace, in stochastic optimal control, and (more recently) in econometrics.
Equilibrium points, linearization; second order systems; contraction mapping principle; existence and uniqueness of solutions to nonlinear differential equations; periodic solutions; Lyapunov stability; the Lure problem; introduction to input-output stability, introduction to nonlinear control techniques.
This is a project course, which is open all ECE MEng students with greater than or equal 80% average, after the completion of at least 3 courses. The MEng student will carry out a 4-month research project under the direct supervision of an ECE faculty member. Faculty members will post the projects offered and interview candidates. At the end of the term, a written Project Report will be submitted and evaluated and graded by the Supervisor. ECE research students (MASc and PhD) are NOT eligible to enroll in this course. MEng students must obtain a permission number to register for this course. ECE 699 is not transferrable to the ECE MASc program.
This course is intended to introduce fundamental concepts and give an overview of recent developments in solid-state photonic devices, as well as their applications in quantum optics and information. These solid-state based photonic devices can be shaped at the nanoscale in order to control the light collection efficiency, integrated in control structures to manipulate their electronic properties, as well as photonic circuits to influence light at the single photon level. Applications include transferring quantum information over long distances for secure communication; generation and detection of non-classical states of light for use in metrology, imaging, and the quantum internet; and the manipulation and storage of quantum information ¿ the fundamental element in a quantum processor.
This course introduces some timely topics in communications security. It covers the advanced topics on cryptography, encryption and authentication, homomorphic encryption, cryptanalysis, provable security, network security mechanisms and protocols, network access authentication, radio air link protection, privacy in radio frequency identification systems, game theory and security in wireless spectrum sharing, attacks, and hardware protections.
This course will help you understand the foundational principles of FPGA architecture, the compilation and CAD process for modern FPGAs, high-level synthesis with OpenCL, communication overlay fabrics, and design strategies and patterns for computational acceleration. In particular, we will explore topics of contemporary interest such as machine learning that can influence both (1) how we design FPGAs, and (2) how they can be accelerated using FPGAs.
Application of formal methods to the verification of computer-based systems. Algebraic and automata preliminaries. Temporal logic and model checking. Decision procedures. Mechanized theorem proving. Advanced topics chosen by the instructor.
As the cost of computing decreases at a phenomenal rate, the use of large format CCD area image sensors increases. Applications of CCD image sensors include industrial such as web inspection, document scanning, manufacturing product inspection for quality and process control, manufacturing product sorting and many other industrial applications. Multimedia and computers increasingly use their CCD image sensors or active pixel CMOS type image sensors. This course will start with the basic theory of CCD image sensors and graduate to CMOS type solid state image sensors. It will concentrate on the state of the art of this field and will deal with the basic device theory, the circuit design and architectures. Photosensitivity, noise, modulation transfer function and other aspects of spatial resolution will be covered. Related Background: E&CE semiconductor and circuit undergraduate courses.
ECE 738Low Power VLSI Circuits for Wireless Communication
This course covers the system level design of integrated circuits for wireless transceivers. Specific mixed analog/digital circuits such as: mixers, A/D and D/A converters (Nyquist rate and oversampled) for IF digitizing as well as switched capacitor filters for IF and baseband processing will be studied. Related Background: Basic knowledge of Analog Integrated Circuits.
The separation of models from the simulation engine. The interaction of models and the simulation engine. Basics of a simulation engine. Mathematical tools for modeling. Modeling using modern Analog Hardware Description Languages (AHDLs). AHDL applications to: large circuit simulation, efficient model development/verification, specialized simulators.
Principles of distributed computing; architectures and middleware; servers, processes, and virtualization; upper-layer network protocols, inter-process communication and remote procedure calling; concurrency, synchronization and distributed algorithms; dependable distributed systems and fault tolerance.
Advanced study of software design and architecture; representation of architecture/design; software design methods; patterns in software design; analysis, assessment, verification and quality control for software design; case studies, current research issues and challenges. Related Background: Basic exposure to programming using C or C++, previous graduate or undergraduate course in software specifications, or software engineering should be sufficient.
Models for concurrent programming; data programming; data parallel models for SIMD and MIMD computers; explicit, semiautomatic, and automatic approaches; data parallel compilers; software engineering issues such as program and data partitioning; task mapping and scheduling, concurrent program design, testing and debugging of concurrent programs, performance tuning, etc. Related Background: Basic exposure to programmin using C or Fortran, previous graduate or undergraduate course in operating system or concurrent programming would be helpful.
This course discusses a broad range of techniques in reducing the negative impact of software bugs to improve software reliability and security. Main topics include: fundamental concepts of software reliability and security, software bug detection and diagnosis, software bug tolerance and recovery, and text analytics.
This course covers the concepts and theory required to understand, design, program, and analyze safety-critical software-intensive real-time systems (and how you get the most out of your deadline-constrained life). The course specifically covers the following topics: challenges and problems of modern embedded software, building blocks of embedded systems, software modeling and design, UML, UML/MARTE, the scheduled model, the synchronous model, worst-case execution time analysis, real-time scheduling theory, interrupt handling for real-time systems, safety analysis and argumentation, and system performance measurement and evaluation.
This course focuses on the protection of various components of a power system including transmission lines, rotating machinery, transformers, busbars, reactors, capacitors and distribution lines. The course will review the fundamental features of a reliable protection system and will discuss the major components of a protection system including current and voltage transformers, circuit breakers, and relays. Various protection strategies such as nonpilot overcurrent protection, nonpilot distance protection, pilot protection and differential protection will be discussed in this course.
This course addresses all the dimensions of Power Quality (PQ) issues including mitigation strategies. The focus is mainly on qualitative concepts and comprehensive coverage. This course introduces PQ definitions, limitations, related international standards and mathematical techniques for PQ analysis of Power Systems. Different identification, localization and classification techniques for PQ problems will be investigated. The various kinds of PQ problems and their effects on load/system equipment will be looked at in detail. Mitigation strategies like passive filtering, active and hybrid power filtering, static VAT compensation, DVR, UPQC, etc. will be investigated. Areas covered include voltage sags, interruptions, transients, flickers, harmonics and modeling and simulation of utility systems. Grounding imperfection as a major cause for PQ problems will be addressed in detail. Moreover, the requirements and impacts of distributed generation (DG) on network power quality will be studies in detail. Effects of DG on voltage regulation, relaying losses, islanding and standards will be examined. Background Required - Basic understanding of modeling of power system elements and analysis techniques. Familiarity wit a programming language and/or a simulation package such as EMTDC/PSCAD and MATLAB is desirable.
Adaptive control is an approach used to deal with the unavoidable problem of plant uncertainty. Rather than providing a fixed linear time-invariant controller, this approach yields a controller whoes parameters change with time. This controller typically consists of a linear time-invariant compensator together with a tuning mechanism which adjusts the controller gains; typical control objectives are stabilization and tracking.The bulk of the course will be centered on an identifier based approach. Here one chooses a model for the plant, whose parameters are unknown, and the plant parameters are recursively estimated; controller gains are computed assuming that the present estimate is corrent. We first study algorithms to carry out parameter estimation, we then look at various control laws, and finally these are combined to yield an adaptive controller. Related Background: knowledge of linear system.
This course provides an overview of the fundamentals and the recent research in the field of humanoid robotics. The course covers kinematics and dynamics, postural stability, control, gait and trajectory generation and inertial parameter estimation. Additional advanced topics in learning, human-robot interaction, manipulation and grasping are introduced.
This course will cover aspects of path planning, dynamic vehicle routing, and coordination for mobile robots. Topics include: 1) Path planning: graph search methods; traveling salesman problems 2) Multi-robot coordination: the consensus and rendezvous problems; sensor coverage; workspace partitioning/load balancing. 3) Dynamic vehicle routing: overview of Poisson processes and birth- death processes; path planning for tasks arriving in real-time; relation to automated material handling, mobility-on-demand.
Monotone and Dynkin class theorems, introduction to discrete and continuous parameter martingales, stochastic integrals, Ito formula, Girsanov transformation. Held with: STAT 902.