The following directory lists the graduate courses which the University expects to offer, although the University in no way guarantees that all such courses will be offered in any given academic year, and reserves the right to alter the list if conditions warrant. Click on the links below for a list of courses in that subject area. You may then click “View Classes” to see scheduled classes for individual courses.
5101. Introduction to System Theory
3.00 credits
Prerequisites: Recommended preparation: ECE 3101.
Grading Basis: Graded
Modeling and analysis of linear systems. Introduction to functions of a complex variable. Linear algebra with emphasis on matrices, linear transformations on a vector space, and matrix formulation of linear differential and difference equations. State variable analysis of linear systems. Transform methods using complex variable theory, and time-domain methods including numerical algorithms.
View Classes »5151. Underwater Acoustics and Sensing Systems
3.00 credits
Prerequisites: Recommended preparation: Undergraduate courses in Calculus Based Physics; MATLAB or equivalent for computer simulations.
Grading Basis: Graded
The fundamentals of ocean acoustics, including the acoustic wave equation, ray theory, acoustic arrays and filters, ambient noise, scattering, absorption, an introduction to normal mode theory, and sonar equations. Computer simulation emphasizes acoustic ray tracing and propagation loss predictions.
View Classes »5201. Electromagnetic Wave Propagation
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Engineering application of Maxwell's field theory to electromagnetic wave propagation in various media. Reflection, refraction, diffraction, dispersion, and attenuation. Propagation in sea water and in the ionosphere.
View Classes »5211. Semiconductor Devices and Models
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Band theory, conduction in semiconductors, carrier statistics, deep levels, impurities with multiple charge states, heavy doping effects, non-uniform doping. Non-equilibrium processes, carrier scattering mechanisms, the continuity equation, avalanche multiplication, carrier generation, recombination, and lifetime. P-n junctions, non-abrupt junctions, various injection regimes, and device models. Metal semiconductor junctions, current transport mechanisms, and models. BJT, JFET, MESFET, and MOSFET, and device models.
View Classes »5212. Fundamentals of Opto-Electronic Devices
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Absorption and emission mechanisms in direct and indirect semiconductors. Semiconductor optoelectronic devices such as light-emitting diodes, injection lasers, photocathodes, solar cells, and integrated optics.
View Classes »5223. Nanophotonics
3.00 credits
Prerequisites: ECE 3223 or consent of instructor.
Grading Basis: Graded
Principles and applications of nanophotonics with focus on optical metamaterials, plasmonics, and photonic bandgap crystals. Topics covered include electric plasma, magnetic plasma, optical magnetism, negative index matematerials, localized and non-localized surface plasmon polaritons, photonic bandgap structures, superlens, optical cloaking, surface enhanced Raman spectroscopy, transformation optics, plasmonic sensors, plasmonic waveguides.
View Classes »5225. Electron Device Design and Characterization
3.00 credits
Prerequisites: Recommended preparation: ECE 4211.
Grading Basis: Graded
Design and evaluation of micro/nano electronic devices using state-of-the-art computer simulation tools, experimental electrical characterization of semiconductor devices and overview of modern electronic devices such as high-performance MOSFETs, TFTs, solar cells, non-volatile memories, CCDs, thermoelectric power generators. The electronic device (such as nanometer scale field effect transistor) design project will involve use of Synopsys tools to simulate the fabrication process, device simulation and performance evaluation.
View Classes »5232. Optoelectronic Devices
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Optoelectronic devices as applied to fiber optic communications, optical switching and interconnects. Semiconductor laser devices, including dc, ac smallsignal, ac large signal, and noise with emphasis upon analytical models. Vertical cavity devices and technology. Semiconductor optical amplifiers, waveguide and vertical cavity modulators, photodetectors, optical switches, receivers and transmitters. Techniques for OE integration and the relevance of bipolar and field-effect devices for monolithic integration. Technologies for optoelectronic integration for telecom and datacom optical interconnect. WDM techniques for optical networks.
View Classes »5242. Micro-Optoelectronic Devices and IC Fabrication
3.00 credits
Prerequisites: ECE 3221 and 4211. Not open for credit for students who have passed ECE 4242.
Grading Basis: Graded
Semiconductor wafer characterization using Hall effect, X-ray diffraction, and Photoluminescence; Semiconductor wafer processing using Diffusion, Oxidation, Epitaxial growth and/or Qdot self-assembly, Photolithographic techniques; Project work including design, modeling and fabrication of solar cells, FETs, Memory, LED and Lasers, sensors, and IC building blocks for digital and analog circuits.
View Classes »5261. Memory Device Technologies
3.00 credits
Prerequisites: This course and ECE 4261 may not both be taken for credit.
Grading Basis: Graded
Current and future digital solid-state memory device technologies including DRAM, SRAM, flash memory, ferroelectric memory, magnetoresistive memory, phase-change memory and resistive memory, with an emphasis on the underlying physical mechanisms.
View Classes »5401. Advanced Digital Systems Design
3.00 credits
Prerequisites: Recommended preparation: coursework in digital design.
Grading Basis: Graded
Microarchitecture and design of hardware acceleration for domain-specific applications. Topics include gate-level design, register-transfer-level (RTL) design, microarchitecture, instruction set architecture, compilers, programming languages, and algorithms. Focus on both efficient software for embedded applications and the design of efficient hardware systems for such applications.
View Classes »5402. Computer Architecture
3.00 credits
Prerequisites: Recommended preparation: CSE 4302 or equivalent.
Grading Basis: Graded
Provides an in-depth understanding of the inner workings of modern digital computer systems. Traditional topics on uniprocessor systems such as performance analysis, instruction set architecture, hardware/software pipelining, memory hierarchy design and input-output systems will be discussed. Modern features of parallel computer systems such as memory consistency models, cache coherence protocols, and latency reducing/hiding techniques will also be addressed. Some experimental and commercially available parallel systems will be presented as case studies.
View Classes »5510. Power System Analysis
3.00 credits
Prerequisites: ECE 2001 or equivalent.
Grading Basis: Graded
Fundamentals of power system planning, operation, and management. Power generation and distribution. Modeling of AC generator, AC and DC motors, transformer and cable. Power flow solution. Modern power system monitoring/control, fault analysis, and transient stability analysis using computer tools. Use of power system simulation tools for power system planning and design.
View Classes »5512. Power Distribution
3.00 credits
Prerequisites: ECE 3231.
Grading Basis: Graded
Principles of distribution system planning, automation and real-time operation with applications. Concepts of AC/DC Electricity. Three-phase power distribution as well as DC and Hybrid circuits. Load flow calculations, fault analysis, and reliability evaluation. Distributed power resources. Distribution system protection and reconfiguration. Smart distribution technologies. Efficient and resilient energy utilization.
View Classes »5520. Advanced Power Electronics
3.00 credits
Prerequisites: ECE 3211.
Grading Basis: Graded
Advanced converter and inverter topologies for high efficiency applications. Non-ideal component characteristics. Necessary components such as gate drive circuits and magnetic component design (that are not covered in introductory power electronics courses).
View Classes »5530. Modeling and Control of Electric Drives
3.00 credits
Prerequisites: ECE 3212.
Grading Basis: Graded
Several topics related to modeling and control of electric drives. Fundamental equations related to inductance and flux variations in a rotating machine, leading to torque production. Reference frame theory and transformations for modeling purposes. Dynamic models of three-phase induction and permanent-magnet synchronous machines. Basic modeling of power electronic converters for electric drives, with focus on three-phase DC/AC inverters. Various control strategies with focus on vector control and different power electronic switching schemes in electric drives.
View Classes »5540. Electrical System Protection and Switchgear
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Methods to sense voltage and current in medium and low voltage applications. Voltage sensing techniques include differential voltage amplifiers, shunt voltage measurement, and potential transformers. Current sensing techniques include current transformers, Rogowski coils, series voltage measurement, and Hall-effect sensors. Solid-state and mechanical relays and timing functions. Fuses and circuit breakers at medium voltage levels with focus on ratings, application-specific selection, and response time. Protection methods, e.g. differential protection, of transformers, generators, and cables with focus on distance relays and specialized devices.
View Classes »5550. Microgrids
3.00 credits
Prerequisites: ECE 3231 or instructor consent.
Grading Basis: Graded
Advanced modeling, control, resilience and security technologies useful for the grid modernization from a unique angle of microgrid design, analysis and operation. Smart inverters, microgrid architectures, distributed energy resources modeling, microgrid hierachical control, microgrid stability, fault management, resilient microgrids through programmable networks, reliable networked microgrids, and cyber security.
View Classes »5552. Communication Systems in Smart Grids
3.00 credits
Prerequisites: ECE 3231.
Grading Basis: Graded
Analysis and design of communications systems to support emerging smart power systems, including transmission and distribution grids. Topics include communication system concepts and principles, control and communication system enhancements, smart grid architecture and applications with different requirements, wide area network (WAN) and field area network (FAN) technologies and data management, smart grid security assessment with operational technologies, robust advanced metering infrastructure (AMI) applications in communication networks design.
View Classes »5554. Distribution Management Systems
3.00 credits
Prerequisites: ECE 3231 or instructor consent.
Grading Basis: Graded
Role of Distribution Management Systems (DMS) in smart distribution, standards and regulations, static and dynamic models, advanced DMS applications (topology processor, Volt/VAR control, fault detection, isolation, restoration, state estimation, three-phase power flow, short circuit analysis, feeder reconfiguration, optimal capacitor placement, protection coordination, maintenance and outage planning), power quality analysis, electric vehicle charging/discharging, active distribution network under high penetration of distributed energy resources (DERs), aggregation of DERs for DERMS.
View Classes »6094. Seminar
1.00 credits | May be repeated for a total of 8 credits.
Prerequisites: None.
Grading Basis: Satisfactory/Unsatisfactory
Presentation and discussion of advanced electrical engineering problems. Students taking this course will be assigned a final grade of S (satisfactory) or U (unsatisfactory).
View Classes »6095. Special Topics in Electrical and Systems Engineering
1.00 - 3.00 credits | May be repeated for a total of 15 credits.
Prerequisites: None.
Grading Basis: Graded
Classroom and/or laboratory courses in special topics as announced in advance for each semester.
View Classes »6099. Independent Study in Electrical Engineering
1.00 - 6.00 credits | May be repeated for a total of 36 credits.
Prerequisites: None.
Grading Basis: Graded
Individual exploration of special topics as arranged by the student with an instructor of his or her choice.
View Classes »6111. Applied Probability and Stochastic Processes
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Statistical methods for describing and analyzing random signals and noise. Random variables, conditioning and expectation. Stochastic processes, correlation, and stationarity. Response of linear systems to stochastic inputs. Applications.
View Classes »6121. Information Theory
3.00 credits
Prerequisites: ECE 6111.
Grading Basis: Graded
Basic concepts: entropy, mutual information, transmission rate and channel capacity. Coding for noiseless and noisy transmission. Universal and robust codes. Information-theoretic aspects of multiple-access communication systems. Source encoding, rate distortion approach.
View Classes »6122. Digital Signal Processing
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Discrete-time signals and systems. The z-transform. The Discrete Fourier Transform (DFT). Convolution and sectioned convolution of sequences. IIR and FIR digital filter design and realization. Computation of the DFT: The Fast Fourier Transform (FFT), algorithms. Decimation and interpolation. Parametric and nonparametric spectral estimation. Adaptive filtering. Finite word length effects.
View Classes »6125. Digital Image Processing
Problems and applications in digital image processing, two-dimensional linear systems, shift invariance, 2-D Fourier transform analysis, matrix Theory, random images and fields, 2-D mean square estimation, optical imaging systems, image sampling and quantization, image transforms, DFT, FFT, image enhancement, two-dimensional spatial filtering, image restoration, image recognition, correlation, and statistical filters for image detection, nonlinear image processing, and feature extraction.
View Classes »6126. Fundamentals of Optical Imaging
Learning optical imaging fundamentals. Topics include: review of two-dimensional linear system theory; scalar diffraction theory, wave optics, Fresnel and Fraunhofer diffraction; imaging properties of lenses; image formation; optical resolution in imaging, frequency analysis of optical imaging systems; imaging with coherent and incoherent sources, coherent transfer function; optical transfer function, point spread function, fundamentals of microscopy, two-dimensional spatial filtering; coherent optical information processing; frequency-domain spatial filter synthesis; holography.
View Classes »6141. Neural Networks for Classification and Optimization
3.00 credits
Prerequisites: None.
Grading Basis: Graded
This course provides students with an understanding of the mathematical underpinnings of classification techniques as applied to optimization and engineering decision-making, as well as their implementation and testing in software. Particular attention is paid to neural networks and related architectures. The topics include: Statistical Interference and Probabilty Density Estimation, Single and Multi-layer Perceptions, Radial Basis Functions, Unsupervised Learning, Preprocessing and Feature Extraction, Learning and Generalization, Decision Trees and Instance-based Classifiers, Graphical Models for Machine Learning, Neuro-Dynamic Programming.
View Classes »6151. Communication Theory
3.00 credits
Prerequisites: ECE 6111.
Grading Basis: Graded
Design and analysis of digital communication systems for noisy environments. Vector representation of continuous-time signals; the optimal receiver and matched filter. Elements of information theory. Quantization, companding, and delta-modulation. Performance and implementation of common coherent and non-coherent keying schemes. Fading; intersymbol interference; synchronization; the Viterbi algorithm; adaptive equalization. Elements of coding.
View Classes »6171. Mobile Robotics
3.00 credits
Prerequisites: Recommended preparation: MATH 2410Q, MATH 3160 or STAT 3345, ECE 3111 and familiarity with MATLAB programming.
Grading Basis: Graded
Coordinate transformation, kinematics and dynamics, sensor modeling, specifics of camera sensors, inertial measurement unit (IMU) sensor, simultaneous localization and mapping (SLAM), EKF-SLAM, Monte Carlo localization, SLAM observability, robot control, specifics of vision-based control, and aspects of Human-robot interaction; class project with a project report.
View Classes »6243. Nanotechnology
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Nanoelectronic and optoelectronic devices: Quantum confinement in 1D, 2D and 3D (quantum wells, wires, and dots) structures; density of states and carrier density in low-dimensional structures; fabrication methodology for quantum wire transistors and lasers; single-electron transistors/tunneling devices; growth and characterization of nanostructured materials with grain sizes in the range of 10-50 nm. Organic monolayers: Langmuir-Blodgett monolayers, Self-Assembled monolayers, Multi-layer structures, technological applications of organic thin films.
View Classes »6244. Nanotechnology - II (Laboratory Course)
3.00 credits
Prerequisites: None.
Grading Basis: Graded
Growth and characterization of carbon nanotubes using vapor phase nucleation; Growth of cladded quantum dots using liquid and/or vapor phase techniques; Characterization using AFM and TEM and Dynamic scattering techniques; Nano-device processing highlighting E-Beam lithography, and self assembly techniques; Project work involving fabrication of devices including LEDs, FETs and memor, detectors and sensors using quantum dots and nanotubes/wires.
View Classes »6421. Advanced VLSI Design
3.00 credits
Prerequisites: Recommended preparation: ECE 3421 and ECE 3302 (or equivalent).
Grading Basis: Graded
Advanced concepts of circuit design for digital VLSI components in state of the art MOS technologies. Emphasis is on the circuit design, optimization, RTL design, synthesis, and layout of either very high speed, high density or low power circuits and systems for use in applications such as micro-processors, signal and multimedia processors, memory and periphery. Other topics include challenges facing digital circuit designers today and in the coming decade, such as the impact of scaling, deep submicron effects, interconnect, signal integrity, power distribution and consumption, and timing.
View Classes »6437. Computational Methods for Optimization
3.00 credits
Prerequisites: ECE 5101.
Grading Basis: Graded
Computational methods for optimization in static and dynamic problems. Ordinary function minimization, linear programming, gradient methods and conjugate direction search, nonlinear problems with constraints. Extension of search methods to optimization of dynamic systems, dynamic programming.
View Classes »6439. Estimation Theory and Comp Algorithms
3.00 credits
Prerequisites: ECE 5101 and 6111.
Grading Basis: Graded
Estimation of the state and parameters of noisy dynamic systems with application to communications and control. Bayesian estimation, maximum-likelihood and linear estimation. Computational algorithms for continuous and discrete processes, the Kalman filter, smoothing and prediction. Nonlinear estimation, multiple model estimation, and estimator Kalman, multiple model estimation, and estimator design for practical problems.
View Classes »