Electrical and Computer Engineering < Lehigh University

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2025-26 Catalog
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Courses, Programs and Curricula
P.C. Rossin College of Engineering and Applied Science
Electrical and Computer Engineering
Electrical and Computer Engineering
WEBSITE:
HTTPS://ENGINEERING.LEHIGH.EDU/ECE
___________________________________________________________________________________________________________________________________________________
The department of electrical and computer engineering (ECE) offers undergraduate and graduate programs of study along with supporting research for students interested in the fields of electrical engineering and computer engineering. Graduate study leads to the degrees, master of science, master of engineering, and doctor of philosophy in electrical engineering, and the master of science and doctor of philosophy in computer engineering.
The undergraduate programs emphasize the fundamental aspects of their respective areas. Engineering design concepts are introduced early in the curriculum, and required instructional laboratories introduce design as a hands-on activity. Electives permit students to tailor their programs according to their interests and goals, whether they be in preparation for graduate study or entry into industry. Students are free to select courses offered by other departments and are encouraged to do so when appropriate. In this way they can prepare themselves for activities which straddle departmental boundaries or for entry into professional schools such as medicine or management. Students  synthesize and apply their knowledge in a senior design project. Students may use the senior design project as a way to participate in the various research projects in the department.
The department maintains a number of laboratories in support of its curricular programs. These laboratories include the sophomore and junior lab, electronic circuits and systems laboratory, microcomputer laboratory, electromechanics laboratory, digital signal processing laboratory, digital systems laboratory and senior projects laboratories.
The department has research laboratories in computer architectures, wireless communications, optoelectronics, compound semiconductors, electron device physics, microelectronics fabrication, signal processing, and communications. These laboratories, among others, are available for undergraduate projects.
The graduate programs allow students to deepen their professional knowledge, understanding, and capability within their subspecialties. Each graduate student develops a program of study in consultation with his or her graduate advisor. Key research thrust areas in the department include:
Microelectronics and Nanotechnology.
Wireless Communications and Networking.
Optoelectronics.
Bio-Engineering.
Graduate research is encouraged in these and other areas.
Computers and computer usage are an essential part of the student’s learning experience. The university provides a distributed network of about 75 high-performance workstations and over 300 PC-compatible microcomputers in public sites throughout the campus. The ECE department has state-of-the-art systems to augment and extend the generally available university systems. There are approximately 90 Workstations running the Microsoft and Linux platforms that are located in various ECE Teaching Labs.  Additionally, there is an ECE Teaching Lab Linux Platform with over 40 servers that are used both for graduate research and to augment classroom learning. The systems provide an array of software for students and researchers, such as Cadence, Synopsys, Silvaco, Anaconda/Python, Nvidia CUDA Development Kit, Matlab, LabView, Xilinx, and many open source applications. The ECE Department workstations and servers are connected via high speed ethernet, which are in turn connected to the university's backbone network, and to the external world through the internet. 2. Students are not required by the department, nor the university, to own a personal computer, but many find such a tool a valuable asset.
A detailed description of the curricular programs follows with a listing of the required courses and with a listing of the departmental course offerings. The departmental courses carry the prefix ECE for electrical and computer engineering. Courses given by the Computer Science and Engineering department have the prefix CSE. Students are urged to search both listings for courses appropriate to their career goals.
Undergraduate Programs
Mission Statement for the Electrical Engineering Program
The mission of the electrical engineering and computer engineering programs is to prepare engineers to meet the challenges of the future, to promote a sense of scholarship, leadership, and service among our graduates, to instill in the students the desire to create, develop, and disseminate new knowledge, and to provide international leadership to the electrical engineering and computer engineering professions.
Program Educational Objectives in Electrical Engineering
It is expected that our alumni will:
be valued as dependable and technically proficient electrical engineers across a wide variety of fields, industries, non-profit organizations, national laboratories, entrepreneurial endeavors or in the pursuit of graduate education,
pursue lifelong learning and professional development to advance their knowledge and skills for successful and rewarding careers,
function and communicate effectively individually and in a team environment, contribute to multi-disciplinary projects, and attain leadership positions in their chosen profession, communities, and the global society, and
function as responsible members of society with an awareness of the professional responsibilities and the global, social and the ethical ramifications associated with their work.
Bachelor of Science in Electrical Engineering
The required courses for this degree contain the fundamentals of linear circuits, systems and control theory, electronic circuits, signal theory, physical electronics, electromagnetic theory, energy conversion, digital systems, and computing techniques. A strong foundation in the physical sciences and in mathematics is required. Approved electives, chosen with the advisor’s consent, are selected in preparation for graduate study or entry into industry according to individual interests.
The program requires a minimum of 125 credit hours, and is a
ccredited by the Engineering Accreditation Commission of ABET,
, under the commission’s General Criteria and Program Criteria for Electrical, Computer, Communications, Telecommunication(s), and Similarly Named Engineering Programs.
The recommended sequence of courses follows:
First Year
First Semester
Credits
Second Semester
Credits
MATH 021
MATH 022
WRT 001
WRT 002
ENGR 005
ECO 001 or HSS Elective
PHY 011
PHY 012
CHM 030
ENGR 010
14
18
Second Year
First Semester
Credits
Second Semester
Credits
ECE 033
ECE 121
ECE 123
ECE 081
ECE 126
PHY 021
PHY 022
ECE 108
MATH 023
MATH 205
17
15
Third Year
First Semester
Credits
Second Semester
Credits
ECE 125
ECE 132
ECE 182
ECE 203
ECE 200
ECE 205
ECE 202
Approved technical electives
MATH 231
ECO 001 or HSS elective
15
15
Fourth Year
First Semester
Credits
Second Semester
Credits
ECE 257
ECE 258
HSS elective
Approved technical electives
Approved technical electives
HSS elective
Free elective
Free elective
16
15
Total Credits: 125
The HSS Advanced Requirement of 12 credits is met with three 4-credit courses in this sequence, and other options are possible. Distribution of HSS courses must satisfy other college requirements.
Approved technical electives are subjects in the area of science and technology. Students must select a minimum of four courses (totaling at least 12 credits) from ECE or CSE course listings, with a minimum of two courses that are designated ECE, at least one engineering elective outside the ECE and CSE listings, and at least one elective in math and natural sciences with the exception of computer science.
Approved Technical Electives for Electrical Engineering
Requirement
Minimum of 4 ECE or CSE elective courses of which at least 2 courses must be designated ECE. Students can choose electives from the courses listed below or from special topics courses that are designated ECE 350. Independent study courses designated ECE 392 could also count towards approved technical electives.
Circuits and Power
ECE 310
Wireless Circuits
ECE 313
Power Electronics
ECE 328
Electricity Economics
ECE 321
Introduction to Power Systems
ECE 322
Introduction to Photovoltaic Energy Systems
ECE 332
Design of Linear Electronic Circuits
ECE 333
Medical Electronics
ECE 337
Introduction to Micro- and Nanofabrication
ECE 355
Mixed Signal Circuits
ECE 361
Introduction to VLSI Circuits
ECE 363
Computer-Aided Design of Digital Systems
ECE 366
Neural Engineering
Communications and Cyber Physical Systems
ECE 212
Control Theory
ECE 327
Communications & Networking for Smart Grids
ECE 339
Graphical Signal Processing
ECE 341
Fundamentals of Wireless Communications
ECE 342
Communication Theory
ECE 345
Fundamentals of Data Networks
ECE 364
Introduction to Cryptography and Network Security
ECE 387
Digital Control
ECE 389
Control Systems Laboratory
Semiconductor Devices and Photonics
ECE 308
Physics and Models of Electronic Devices
ECE 309
Applied Quantum Engineering
ECE 325
Semiconductor Lasers I
ECE 348
Fundamentals of Photonics
ECE 368
Introduction to Biophotonics and Optical Biomedical Imaging
ECE 375
Semiconductor Optoelectronics
Learning and Artificial Intelligence
ECE 303
Accelerated Computing for Deep Learning
ECE 306
Autonomous Driving and Robotic Racing
ECE 340
Introduction to Online and Reinforcement Learning
ECE 343
Digital Signal Processing
ECE 344
Statistical Signal Processing
Computers
Any CSE course except
CSE 003
CSE 004
CSE 007
CSE 012
, or
CSE 252
ECE 201
Computer Architecture
ECE 303
Accelerated Computing for Deep Learning
ECE 305
Memory Systems
ECE 306
Autonomous Driving and Robotic Racing
ECE 319
Digital System Design
ECE/CSE 336
Embedded Systems
ECE 340
Introduction to Online and Reinforcement Learning
ECE 345
Fundamentals of Data Networks
ECE 364
Introduction to Cryptography and Network Security
Minor in Electrical Engineering
The purpose of the Electrical Engineering minor is to enable students to supplement their major with knowledge and skills that increase their ability to realize their multi-disciplinary goals and/or make them more marketable upon graduation.
Required Courses
ECE 081
Principles of Electrical Engineering
or
ECE 083
ECE 162
Introduction to Electrical Engineering
and Electrical Laboratory
ECE 108
Signals and Systems
ECE 121
Electronic Circuits Laboratory
ECE 123
Electronic Circuits
Select one of the following Electrical and Computer Engineering Courses or Other Approved Elective:
3-4
ECE 033
Introduction to Computer Engineering
ECE 125
Random Signals and Learning
ECE 126
Fundamentals of Semiconductor Devices
ECE 339
Graphical Signal Processing
ECE 341
Fundamentals of Wireless Communications
ECE 343
Digital Signal Processing
ECE 371
Optical Information Processing
ECE 372
Optical Networks
Total Credits
16-17
ECE 083
and
ECE 162
plus departmental approval.
Mechanical Engineering substitute
ME 245
Engineering Vibrations for
ECE 108
, by petition, but must select an additional ECE elective. Because of similar course requirements between electrical and computer engineering majors, computer engineering students wishing to minor in electrical engineering can use one required course in their major and must choose four electives, excluding required courses, from the above list to satisfy the requirements of the electrical engineering minor. Computer engineering technical electives (chosen from the above list) can be used to satisfy the requirements of the minor.
Technical minors must be declared by the end of pre-registration of the student’s sixth semester. If course requirements change or a student wishes to vary the list of courses above, a revised minor declaration form must be submitted.
Bachelor of Science in Computer Engineering
See catalog entry for
Computer Engineering
Graduate Programs
Graduate programs of study provide a balance between formal classroom instruction and research and are tailored to the individual student’s professional goals. The programs appeal to individuals with backgrounds in electrical or computer engineering, mathematics, or the physical sciences. Research is an essential part of the graduate program.
The Master of Engineering degree requires the completion of 30 credit hours of work. A program of study must be submitted in compliance with the college rules.
The Ph.D. degree in electrical engineering requires the completion of 42 credit hours of work (including the dissertation) beyond the master's degree (48 hours if the master's degree is non-Lehigh), the passing of a departmental qualifying examination appropriate to each degree within two years after entrance into the degree program, the passing of a general examination in the candidate's area of specialization, the admission into candidacy, and the writing and defense of a dissertation. Competence in a foreign language is not required.
The Master of Science degree requires the completion of 30 credit hours of work that may include a six credit thesis or a six credit independent study. A program of study must be submitted in compliance with the graduate school regulations.
The ECE Department has a core curriculum requirement for graduate students in each of the degree programs. The purpose of this requirement is to guarantee that all students pursuing graduate studies in the department acquire an appropriate breadth of knowledge of their discipline.
Electrical Engineering
To satisfy the core curriculum requirements in Electrical Engineering students must select three courses from the following five different areas:
ECE 401
Advanced Computer Architecture
ECE 402
Advanced Electromagnetics
ECE 414
Statistical Decision Making and Machine Learning Theory
or
ECE 441
Fundamentals of Wireless Communications
ECE 420
Advanced Circuits and Systems
ECE 451
Physics of Semiconductor Devices
Computer Engineering
See catalog entry for
Computer Engineering
M.S. in Photonics
The Masters of Science degree in Photonics is an interdisciplinary degree that is designed to provide students with a broad training experience in the various aspects of photonics, including topics in Physics, Electrical Engineering and Materials Science and Engineering. It covers both theoretical and practical topics in areas such as fiber optics, integrated optics, lasers, nonlinear optics and optical materials to prepare the students to work in industry directly after graduation. The program is also designed so as to make it possible for students who wish to continue on for a Ph.D. to still satisfy the requirements of their individual departments for the more advanced degree. For details on this program, see the separate catalog section under Interdisciplinary Graduate Study and Research.
Courses
ECE 033
Introduction to Computer Engineering
0,4
Credits
Analysis, design and implementation of small digital circuits. Boolean algebra. Minimization techniques, synchronous sequential circuit design, number systems and arithmetic. Microcomputer architecture and assembly level programming.
Prerequisites:
CSE 017
or
ENGR 010
ECE 081
Principles of Electrical Engineering
0,4
Credits
Circuit elements and laws. Behavior of simple linear networks, include equivalent circuits and solution techniques. Solution of DC circuits and AC circuits using phasor techniques. Introduction to operational amplifiers. Steady state and transient response of simple circuits. Includes a weekly session for review and discussion. May not be taken with
ECE 083
for credit.
Prerequisites:
MATH 022
and
PHY 021
Can be taken Concurrently:
PHY 021
ECE 083
Introduction to Electrical Engineering
Credits
Circuit elements and laws. Behavior of simple linear networks. Characteristics of electronic circuits and modeling. Introduction to functional circuits, such as operational amplifiers, instrumentation amplifiers, and power systems. Introduction to basic filters and data converters. May not be taken with
ECE 081
for credit.
Prerequisites:
MATH 022
and
PHY 021
Can be taken Concurrently:
PHY 021
ECE 108
Signals and Systems
0,4
Credits
Continuous and discrete signal and system descriptions using signal space and transform representations. Includes Fourier series, continuous and discrete Fourier transforms, Laplace transforms, and z-transforms. Introduction to sampling.
Prerequisites:
ECE 081
ECE 121
Electronic Circuits Laboratory
0,2
Credits
One lecture and one laboratory per week. Experiments illustrating the principles of operation of electronic devices and their circuit applications. Basic electronic instrumentation and measurement techniques.
Prerequisites:
ECE 081
ECE 123
Electronic Circuits
Credits
Methods for analyzing and designing circuits containing electronic devices. Topics include device models, basic amplifier configurations, operating point stabilization, frequency response analysis, and computer-aided analysis of active circuits.
Prerequisites:
ECE 081
ECE 125
Random Signals and Learning
Credits
Introduction to random signals and analysis of linear time invariant (LTI) system response to random inputs. Modeling LTI systems using state space approach. Introduction to inference and learning, including basics of signal detection and estimation, linear regression, and linear time series models.
Prerequisites:
ECE 108
and (
MATH 231
or
MATH 263
Can be taken Concurrently:
MATH 231
MATH 263
ECE 126
Fundamentals of Semiconductor Devices
Credits
Introduction to the physics of semiconductors in terms of atomic bonding and electron energy bands in solids. Charge carriers in semiconductors and carrier concentration at thermal equilibrium. Principles of electron and hole transport, drift and diffusion currents, generation and recombination processes, continuity. Treatment of semiconductor devices including p-n junctions, bipolar junction transistors and field effect transistors.
Prerequisites:
ECE 081
ECE 128
FPGA Laboratory
0,3
Credits
Implementation issues and techniques for digital logic design; combinational and sequential logic design using digital ICs; hardware description languages; field programmable gate arrays (FPGAs); designs with modular building blocks; and functional simulations will be covered in this course.
Prerequisites:
ECE 033
ECE 132
Microcontroller Laboratory
0,3
Credits
Basic digital logic and circuitry. Architecture of microcontrollers. Number conversion and data encoding in microcontrollers. Input and output of microcontrollers. Timers and interrupt routines. Serial communication protocols. Data acquisition, control, sensors, and actuators. Basic software techniques of programming microcontrollers.
Prerequisites:
ECE 033
ECE 162
Electrical Laboratory
Credit
Experiments on circuits, machines, and electronic devices. Elementary network theory. Survey laboratory for students not majoring in electrical or computer engineering.
Prerequisites:
ECE 081
or
ECE 083
Can be taken Concurrently:
ECE 081
ECE 083
ECE 182
Junior Laboratory
Credit
Experiments designed to exploit the students understanding of basic circuits and filters. Experiments designed to help students understand basic signals and systems concepts such as time-frequency domain duality, power measurement, modulation, sampling and data conversion. Students are introduced to a variety of integrated circuits including multipliers, analog switches, digital electronics, S/H, A/D, and D/A converters. Computer software design aids, especially Spice and LabView, are used throughout the semester. One three-hour laboratory per week.
Prerequisites:
ECE 033
and
ECE 121
and
ECE 123
ECE 200
Electrical and Computer Engineering Seminar
Credit
This course provides a comprehensive overview of the field of Electrical and Computer Engineering. Different research areas in the field will be discussed through weekly seminars. The seminars will cover relevant and cutting edge topics in signal processing and machine learning, communication and cyber physical systems, high performance computing and computing architectures, semiconductors and quantum engineering, electronic circuits and power systems, and bio-electrical engineering.
ECE 201
Computer Architecture
Credits
Structure and function of digital computers. Computer components and their operations. Computer interconnection structures. Memory system and cache memory. Interrupt driven input/output and direct memory access. Instruction sets and addressing modes. Instruction pipelining. Floating-point representation and arithmetic. Alternative architectures: RISC vs. CISC and introduction to parallel architectures.
Prerequisites:
ECE 033
ECE 202
Introduction to Electromagnetics
Credits
Elements of vector analysis, Coulomb’s law, Biot-Savart’s and Ampere’s laws, Lorentz Forces, Laplace’s, and Maxwell’s equations, boundary conditions, methods of solution in static electric and magnetic fields, including finite element numerical approach. Quasistationary fields, inductance.
Prerequisites:
MATH 205
and
PHY 021
ECE 203
Introduction to Electromagnetic Waves
Credits
Uniform plane waves in free space and in materials, skin effect. Waves in transmission lines and waveguides, including optical fibers. Energy and power flow, Poynting’s theorem. Reflection and refraction. Resonators. Radiation and diffraction.
Prerequisites:
ECE 202
ECE 205
C/C++ Programming
Credits
Introduction to C/C++ programming language and algorithms to solve engineering problems. Topics include data types, operators, flow control statements, loops, functions, structures, classes, and search and sort algorithm. Several programming projects are assigned throughout the course.
Prerequisites:
ENGR 010
ECE 212
Control Theory
Credits
Introduction to feedback control. Dynamic analysis of linear feedback systems in the time and frequency domain, with emphasis on stability and steady-state accuracy. Major analytical tools: signal-flow graphs, root-locus methods. Nyquist plot, Bode analysis. Cascade compensation techniques.
Prerequisites:
ECE 125
ECE 256
Honors Project
Credit
Open by invitation only to students who have completed
ECE 257
, Senior Project. Selection is based upon the quality of the senior project with regard to ingenuity, design approach and completeness. The objective of this course is to carry the successful senior projects forward to completion of a technical paper suitable for publication or submission to a technical conference. A written paper and oral presentation are required by mid-semester. Oral presentations will be made before an appropriate public forum. Enrollment limited.
ECE 257
Senior Lab I
Credits
With
ECE 258
, provides a complete design experience for Electrical and Computer Engineers. Students are expected to identify essential project aspects crucial to success and to perform in-depth engineering evaluation and testing demonstrating that desired results can be achieved with the proposed implementation. Instruction in technical writing, product development, ethics and professional engineering, and presentation of design and research. Two three hour sessions and one additional two hour lecture per week. Must have senior status.
ECE 258
Senior Lab II
Credits
Continuation of
ECE 257
. Complete design, construction, and testing of projects selected and developed in
ECE 257
. Present final design reviews and project presentations. Submit a final written report. Discuss development issues, including manufacturability, patents, and ethics. Two three-hour sessions per week.
Prerequisites:
ECE 257
ECE 300
Apprentice Teaching
1-4
Credits
ECE 303
Accelerated Computing for Deep Learning
Credits
Graphics Processing Unit (GPU) versus Computer Processing Unit (CPU), hardware architecture of parallel computers, memory allocation and data parallelism, multidimensional kernel configuration, kernel-based parallel programming, principles and patterns of parallel algorithms, application of parallel computing to deep learning neural networks. Deep Learning (DL) algorithms, such as Convolutional Neural Networks (CNN), Stochastic Gradient Descent, and back propagation algorithms. Students may not obtain credit for more than one of
ECE 303
ECE 403
, and
DSCI 421
Prerequisites:
CSE 017
or
ECE 205
ECE 305
Memory Systems
Credits
Cache and memory internal implementations, timing constraints, high-performance memory controllers, advanced memory interfaces, emerging memory technologies, 3D stacked memories, and processing-in-memory architectures. Reviews of state-of-the-art research topics on energy, performance, and reliability issues in cache and memory systems.
Prerequisites:
ECE 201
ECE 306
Autonomous Driving and Robotic Racing
0,3
Credits
Basic framework of autonomous robots; drive train, vehicle controls, and dynamics models; perception subsystems including sensors such as sonar, Lidar, camera, or inertial measurement units (IMU); Robotic Operating Systems (ROS), racing simulators, autonomous driving methods including reactive and deliberative methods; simultaneous localization and mapping (SLAM); path planning and race-line optimization; learning and vision with image classification and obstacle detection.
Prerequisites:
ECE 108
and (
MATH 205
or
CSE 140
ECE 308
Physics and Models of Electronic Devices
Credits
Physics of metal-semiconductor junction, p-n junctions, and MOS capacitors. Models of Schottky barrier and p-n junction diodes, JFET, MOSFET, and bipolar transistors.
Prerequisites:
ECE 126
ECE 310
Wireless Circuits
Credits
Theory and design of high-frequency circuits for wireless communications. Transmission lines and microwave networks. Types of circuits explored include filters, amplifiers, mixers, voltage controlled oscillators (VCOs), phase locked loops (PLLs), synthesizers, modulators and demodulators, and antennae. Design using scattering parameters, Smith chart and RF/microwave CAD programs for simulation. System performance analysis based on noise figure, antenna gain and the Friis equation will be developed. Modulation techniques of AM, FM, PM, and QPSK systems will be compared based on bit error rates (BER) calculated from system parameters.
Prerequisites:
ECE 203
ECE 313
Power Electronics
Credits
Introduction to power semiconductor devices, circuits, and applications. Diodes, thyristors, bipolar and MOS transistors, IGBTs, and other emerging types, and their use in typical power conversion circuits such as rectifiers, buck and boost converters, and dc-dc, dc-ac, and ac-ac inverters and converters. Application examples in motor drives, power supplies and HVDC transmission.
Prerequisites:
ECE 081
ECE 314
Statistical Decision Making and Machine Learning Theory
Credits
To teach the statistical theory describing the performance of general Machine Learning and Statistical Decision Making approaches. We will not attempt to describe details of specific machine learning algorithms, code those algorithms and test them on real data. Students will learn some needed hypothesis testing theory and estimation theory that is necessary to understand learning theory. Students will learn Probably Approximately Correct learning theory. Credit will not be given for both
ECE 314
and
ECE 414
Prerequisites:
ECE 108
and (
MATH 231
or
MATH 309
ECE 318
Introduction to Internet of Things
Credits
Basic framework of the Internet of Things (IoT) including both hardware and software, with principles and applications. Principles cover IoT architecture, embedded systems, technology standards, wireless protocols, and device and network cybersecurity. Application aspects include hands-on experiments with IoT devices, power consumption and low-power modes, sensors and actuators, narrowband Radio Frequency (RF) communications, and IoT applications. Credit will not be given for both
ECE 318
and
ECE 418
Prerequisites:
ECE 132
or
ECE 108
or
ECE 201
or
CSE 202
ECE 319
Digital System Design
Credits
Design techniques at the register transfer level. Control strategies for hardware architectures. Implementation of microprogramming, intersystem communication and peripheral interfacing. Hardware design languages and their use in design specification, verification and simulation.
Prerequisites:
ECE 132
ECE 321
Introduction to Power Systems
Credits
Power systems engineering relating to generation, transmission, distribution and utilization of electric power. This course introduces basic yet critical concepts of large-scale power systems. Topics include power system modeling, power flow, symmetrical faults, unsymmetrical faults, transient stability, and optimal power flow. Subject material is useful to students who pursue careers or research in electric power systems.
Prerequisites:
ECE 123
ECE 322
Introduction to Photovoltaic Energy Systems
Credits
Basic principles for design, installation, and operation of photovoltaic energy systems. Properties of sunlight and physics of photovoltaic cells. Photovoltaic cells, modules, and arrays. Inverters and other system components. Site assessment. Design and installation of grid-connected and stand-alone PV systems. Systems operation. Maintenance, performance, and economic analysis. Relevant design and simulation tools are introduced.
Prerequisites:
ECE 081
ECE 325
Semiconductor Lasers I
Credits
Review of elementary solid-state physics. Relationships between Fermi energy and carrier density and leakage. Introduction to optical waveguiding in simple double-heterostructures. Density of optical modes, Blackbody radiation and the spontaneous emission factor. Modal gain, modal loss, and confinement factors. Einstein’s approach to gain and spontaneous emission. Periodic structures and the transmission matrix. Ingredients. A phenomenological approach to diode lasers. Mirrors and resonators for diode lasers. Gain and current relations. Credit will not be given for both
ECE 325
and
ECE 425
Prerequisites:
ECE 203
ECE 326
Semiconductor Lasers II
Credits
Continuation of Semiconductor Lasers I. Topics covered include: Gain and current relations; dynamic effects; perturbation and coupled-mode theory; dielectric waveguides; and photonic integrated circuits. Credit will not be given for both
ECE 326
and
ECE 426
Prerequisites:
ECE 325
ECE 327
Communications & Networking for Smart Grids
Credits
Overview of smart grid electricity systems. Concepts covered include power system background and operations, electricity markets, legacy grid communications, and the smart grid vision and objectives. Additional focus on relevant communications and networking technologies that enable smart grid applications, such as real-time grid monitoring, automated control, demand response, distributed energy systems, microgrids, vehicle-to-grid integration, and smart homes and buildings. Credit will not be given for both
ECE 327
and
ECE 427
Prerequisites:
ECE 108
ECE 328 (ECO 328)
Electricity Economics
Credits
The course is intended primarily for students who are interested in an exploration of electricity markets around the world, risk management, operation, and the main considerations in the wake of a smart grid implementation as well as in the transition to a low carbon economy.
Repeat Status:
Course may be repeated.
Prerequisites:
ECO 001
and (
MATH 023
or
ECO 146
Attribute/Distribution:
CC, Q, SS
ECE 329
Power System Modeling and Computation
Credits
A comprehensive study of various computational methods that form the basis of many analytical studies of power systems. Topics include power system modeling, solution of linear systems, systems of nonlinear equations, sparse matrix solution techniques, numerical integration, optimization, and their applications in power system analysis. Students are enabled to make informed decisions in their use of commercial software packages and correctly interpret the results. Matlab is used extensively.
ECE 329
and
ECE 429
may not both be taken for credit.
Prerequisites:
ECE 321
or
ECE 421
ECE 332
Design of Linear Electronic Circuits
Credits
Design concepts and topologies. Opamps, differential amplifier, programmable instrumentation amplifier, opamp integrator, differentiator, opamp summer, subtractor, logarithmic amplifier, antilog amplifier, analog multiplier, divider, square rooter, voltage to current converter, voltage- controlled amplifier, current amplifier, current to voltage converter, induction simulator, precision rectifier, regulated power source, comparator, peak detector, sample and hold circuit, clipper circuit, clamper circuit. Hartley oscillator. Audio amplifiers. Equalizer, filter, preamplifier, power amplifier.
Prerequisites:
ECE 123
ECE 333
Medical Electronics
Credits
Bioelectric events and electrical methods used to study and influence them in medicine, electrically excitable membranes, action potentials, electrical activity of muscle, the heart and brain, bioamplifiers, pulse circuits and their applications.
Prerequisites:
ECE 123
ECE 336 (CSE 336)
Embedded Systems
Credits
Use of small computers embedded as part of other machines. Limited-resource microcontrollers and state machines from high level description language. Embedded hardware: RAM, ROM, flash, timers, UARTs, PWM, A/D, multiplexing, debouncing. Development and debugging tools running on host computers. Real-Time Operating System (RTOS) semaphores, mailboxes, queues. Task priorities and rate monotonic scheduling. Software architectures for embedded systems.
Prerequisites:
CSE 017
ECE 337
Introduction to Micro- and Nanofabrication
Credits
Survey of the standard IC fabrication processes, such as photolithography, dry and wet etching, oxidation, thin-film deposition and chemical mechanical polishing. In-depth analysis of MEMS-specific processes such as wafer bonding, wet anisotropic etching, photolithography using thick photoresist, and deep reactive ion etching of silicon. The basics of nanofabrication techniques. The fundamentals of MEMS design will be outlined. A wide variety of MEMS and NEMS devices will be discussed.
Prerequisites:
MAT 033
and
MATH 231
ECE 338
Quantum Electronics
Credits
Electromagnetic fields and their quantization. propagation of optical beams in homogeneous and lens-like media. Modulation of optical radiation. Coherent interactions of radiation fields and atomic systems. Introduction to nonlinear optics-second-harmonic generation. Parametric amplification, oscillation, and fluorescence. Third-order optical nonlinearities. Credit will not be given for both
ECE 338
and
ECE 438
Prerequisites:
ECE 203
ECE 339
Graphical Signal Processing
Credits
Application of graphical programming to mathematical principles in data analysis and signal processing. Review of digital signal processing, use of structures, arrays, charts, building virtual instruments, graphical programming for linear algebra, curve fitting, solving differential and difference equations, signal generation, DFT and FFT analysis, windowing and filtering.
Prerequisites:
ECE 108
ECE 340
Introduction to Online and Reinforcement Learning
Credits
Review of probability and random processes, basic reinforcement learning framework, learning from streaming data, actions in response to changing environment through Markov Decision Processes, elements of artificial intelligence. Exploration-Exploitation tradeoffs through bandit problems, and different methods for reinforcement learning including dynamic programming, Monte Carlo methods, temporal difference and Q-learning. Approximate solutions for very large state space systems, policy iteration and actor critic methods, introduction of deep reinforcement learning. Credit will not be given for both
ECE 340
and
ECE 440
Prerequisites:
MATH 231
or
MATH 309
ECE 341
Fundamentals of Wireless Communications
Credits
Overview of wireless communication systems basics. Cellular concept and other wireless systems. System design fundamentals. Mobile Radio Propagation Modeling: Flat, Frequency Selective, Fast, Slow fading channels, Path Loss Models. Multiple access. Modulation Techniques for wireless. Introduction to wireless networking. Wireless systems and standards. Future wireless systems.
Prerequisites:
ECE 108
ECE 342
Communication Theory
Credits
Theory and application of analog and digital modulation. Sampling theory with application to analog-to-digital and digital-to-analog conversion techniques. Time and frequency division multiplexing. Introduction to random processes including filtering and noise problems. Introduction to statistical communication theory with primary emphasis on optimum receiver principles.
Prerequisites:
ECE 108
and (
MATH 309
or
MATH 231
ECE 343
Digital Signal Processing
Credits
Study of orthogonal signal expansions and their discrete representations, including the Discrete Fourier Transform and Walsh-Hadamard Transform. Development of fast algorithms to compute these, with applications to speech processing and communication. Introduction to the z-transform representation of numerical sequences with applications to input/output analysis of discrete systems and the design of digital filters. Analysis of the internal behavior of discrete systems using state variables for the study of stability, observability and controllability.
Prerequisites:
ECE 108
ECE 344
Statistical Signal Processing
Credits
Introduction to random processes, covariance and spectral density, time average, stationarity, and ergodicity. Response of systems to random inputs. Sampling and quantization of random signals. Optimum filtering, estimation, and hypothesis testing.
Prerequisites:
ECE 108
) and (
MATH 231
or
MATH 309
ECE 345
Fundamentals of Data Networks
Credits
Analytical foundations in the design and evaluation of data communication networks. Fundamental mathematical models underlying network design with their applications in practical network algorithms. Layered network architecture, queuing models with applications in network delay analysis, Markov chain theory with applications in packet radio networks and dynamic programming with applications to network routing algorithms. Background on stochastic processes and dynamic programming will be reviewed.
Prerequisites:
MATH 231
and
ECE 125
ECE 347
Introduction to Integrated Optics
Credits
Theory of dielectric waveguides (ray and wave approach). Modes in planar slab optical guides and in waveguides with graded index profiles. Coupled-mode formalism and periodic structures. Coupling of optical beams to planar structures. Switching and modulation of light in dielectric guides: phase, frequency and polarization modulators; electro-optic, acousto-optic and magneto-optic modulators. Semiconductor lasers. Fabrication of semiconductor components. Recent advances.
Prerequisites:
ECE 202
and
ECE 203
ECE 348
Fundamentals of Photonics
Credits
Concepts of generation, transmission, modulation, and detection of electromagnetic-waves. Paraxial rays and Gaussian beams in uniform media. Wave propagation in integrated waveguides and optical-fibers. Optical-cavity resonators. Light-matter interaction, absorption and amplification of radiation, spontaneous and stimulated-emission. Theory of laser-oscillation and linewidth-narrowing. Wave propagation in anisotropic media. Optical components such as waveplates, optical-couplers and isolators, electro-optic modulators, and photodetectors. Devices with periodic media such as Bragg-reflectors and distributed-feedback lasers. Credit will not be given for both
ECE 348
and
ECE 448
Prerequisites:
ECE 203
ECE 350
Special Topics
Credits
Selected topics in the field of electrical and computer engineering not included in other courses.
Repeat Status:
Course may be repeated.
ECE 355
Mixed Signal Circuits
Credits
Analysis and design of contemporary mixed signal electronic circuits, including phase-locked loops, A/D and D/A converters, sigma-delta converters, and switching power supplies. Continuous and discrete time simulation of mixed signal systems starting with operational amplifiers as a prototype feedback system using Spice and Matlab.
Prerequisites:
ECE 108
and
ECE 123
ECE 361
Introduction to VLSI Circuits
Credits
The design of Very Large Scale Integrated (VLSI) Circuits, with emphasis on CMOS Standard Cell design. Topics include MOS transistor physics, device behavior and device modeling, MOS technology and physical layout, design of combinational and sequential circuits, static and dynamic memories, and VLSI chip organization. The course includes a design project using CAE tools for layout, design rule checking, parameter extraction, and SPICE simulations for performance prediction. Two one-hour lectures and three hours of laboratory per week.
Prerequisites:
ECE 123
ECE 363
Computer-Aided Design of Digital Systems
0,3
Credits
Modern digital chip design, with emphasis on key design concepts, methodology and flow using state-of-the-art electronic design automation (EDA) tools and standard cell libraries from the semiconductor industry. Topics include CMOS transistor operations, interconnect, dynamic/leakage power, delay, RTL coding, logic synthesis, static timing analysis, formal verification, RTL/gate level simulation and physical design. The course consists of a set of labs and a project built upon multiple Synopsys EDA tools, including Design Compiler, PrimeTime, Formality, VCS etc.
Prerequisites:
ECE 033
ECE 364
Introduction to Cryptography and Network Security
Credits
Introduction to cryptography, classical cipher systems, cryptanalysis, perfect secrecy and the one time pad, DES and AES, public key cryptography covering systems based on discrete logarithms, the RSA and the knapsack systems, and various applications of cryptography. May not be taken with
ECE 464
for credit. Must have junior or senior standing.
ECE 366 (BIOE 366)
Neural Engineering
Credits
Neural system interfaces for scientific and health applications. Basic properties of neurons, signal detection and stimulation, instrumentation and microfabricated electrode arrays. Fundamentals of peripheral and central neural signals and EEG, and applications such as neural prostheses, implants and brain-computer interfaces. Closed to students who have taken
BIOE 366
BIOE 466
, and
ECE 466
Prerequisites:
ECE 081
ECE 368 (BIOE 368)
Introduction to Biophotonics and Optical Biomedical Imaging
Credits
Optical principles, techniques, and instruments used in biomedical research and clinical medicine. Fundamental concepts of optical imaging and spectroscopy systems, and details of light-tissue interaction. Commercial devices and instruments, as well as novel optical imaging technologies in development. Closed to students who have taken
ECE 468
BIOE 368
, or
BIOE 468
Prerequisites:
ECE 202
or
PHY 212
ECE 371
Optical Information Processing
Credits
Introduction to optical information processing and applications. Interference and diffraction of optical waves. 2D optical matched filters that use lenses for Fourier transforms. Methods and devices for modulating light beams for information processing, communications, and optical computing. Construction and application of holograms for optical memory and interconnections.
Prerequisites:
ECE 108
and
ECE 202
ECE 372
Optical Networks
Credits
Study the design of optical fiber local, metropolitan, and wide area networks. Topics include: passive and active photonic components for optical switching, tuning, modulation and amplification; optical interconnection switches and buffering; hardware and software architectures for packet switching and wavelength division multiaccess systems. The class is supported with a laboratory.
Prerequisites:
ECE 081
and
ECE 202
ECE 373
Machine Learning for Smart Grid Dynamics and Control
Credits
Introduction to smart grids, microgrids and their components, control of microgrids, introduction to neural networks and deep learning, deep learning for solving optimization problems in smart grids, machine learning based economic dispatch and optimal power flow, control of distributed energy resources, grid following and grid forming control of renewable energy, data-driven model identification using statistical learning, machine learning based control of distributed energy resources. Credit may not be given for both
ECE 373
and
ECE 473
Prerequisites:
MATH 205
ECE 375
Semiconductor Optoelectronics
Credits
Theory and practical implementation of semiconductor optoelectronic devices. Broad coverage of the fundamentals of the propagation, modulation, generation, and detection of light. Topics include the energy transfer between photons and electron-hole pairs, light emission and absorption, radiative and non-radiative processes, electrical and optical characteristics, carrier diffusion and mobility, light extraction and trapping. Specific devices include laser diodes, light-emitting diodes, electroabsorption modulators, photodetectors, and solar cells. Credit will not be given for both
ECE 375
and
ECE 475
Prerequisites:
ECE 126
and
ECE 202
ECE 377
Introduction of Electrical Machines
Credits
Comprehensive review of AC electrical circuits, magnetic circuits, and fundamental electromagnetic principles; modeling, testing, and analysis of single-phase and three-phase transformers; models and operational characteristics of various types of DC machines; introduction to fundamental concepts of AC machines; principles and performance analysis of synchronous generators, synchronous motors, and induction motors. Credit may not be given for both
ECE 377
and
ECE 477
Prerequisites:
ECE 081
ECE 387 (CHE 387, ME 387)
Digital Control
Credits
Sampled-data systems; z-transforms; pulse transfer functions; stability in the z-plane; root locus and frequency response design methods; minimal prototype design; digital control hardware; discrete state variables; state transition matrix; Liapunov stability; state feedback control.
Prerequisites:
CHE 386
or
ECE 212
or
ME 343
ECE 389 (CHE 389, ME 389)
Control Systems Laboratory
Credits
Experiments on a variety of mechanical, electrical and chemical dynamic control systems. Exposure to state of the art control instrumentation: sensors, transmitters, control valves, analog and digital controllers. Emphasis on comparison of theoretical computer simulation predictions with actual experimental data. Lab teams will be interdisciplinary.
Prerequisites:
CHE 386
or
ECE 212
or
ME 343
ECE 392
Independent Study
1-3
Credits
An intensive study, with report of a topic in electrical and computer engineering which is not treated in other courses. Consent of instructor required.
Repeat Status:
Course may be repeated.
ECE 401 (CSE 401)
Advanced Computer Architecture
Credits
Design, analysis and performance of computer architectures; high-speed memory systems; cache design and analysis; modeling cache performance; principle of pipeline processing, performance of pipelined computers; scheduling and control of a pipeline; classification of parallel architectures; systolic and data flow architectures; multiprocessor performance; multiprocessor interconnections and cache coherence.
Prerequisites:
ECE 201
ECE 402
Advanced Electromagnetics
Credits
This course introduces electromagnetic fields from the engineering perspective, aiming at practical applications in the near-field area. Typical topics include vector analysis, electric fields, steady and time-varying magnetic fields, and electromagnetic material properties. The near-field application examples in wireless power transmission will be explained through the derivation in both magnetic and electric fields resonance. The numerical simulation method and software tools for electromagnetic fields analysis will also be introduced in this course.
Prerequisites:
ECE 202
and
ECE 203
ECE 403
Accelerated Computing for Deep Learning
Credits
Graphics Processing Unit (GPU) versus Computer Processing Unit (CPU), hardware architecture of parallel computers, memory allocation and data parallelism, multidimensional kernel configuration, kernel-based parallel programming, principles and patterns of parallel algorithms, application of parallel computing to deep learning neural networks. Deep Learning (DL) algorithms, such as Convolutional Neural Networks (CNN), Stochastic Gradient Descent, and back propagation algorithms. Students may not obtain credit for more than one of
ECE 303
ECE 403
, and
DSCI 421
ECE 404 (CSE 404)
Computer Networks
Credits
Study of architecture and protocols of computer networks. The ISO model; network topology; data-communication principles, including circuit switching, packet switching and error control techniques; sliding window protocols, protocol analysis and verification; routing and flow control; local area networks; network interconnection; topics in security and privacy.
ECE 405
Memory Systems
Credits
Cache and memory internal implementations, timing constraints, high-performance memory controllers, advanced memory interfaces, emerging memory technologies, 3D stacked memories, and processing-in-memory architectures. Reviews of state-of-the-art research topics on energy, performance, and reliability issues in cache and memory systems. Credit may not be given for both
ECE 305
and
ECE 405
Prerequisites:
ECE 201
ECE 406
Autonomous Driving and Robotic Racing
0,3
Credits
Basic framework of autonomous robots; drive train, vehicle controls, and dynamics models; perception subsystems including sensors such as sonar, Lidar, camera, or inertial measurement units (IMU); Robotic Operating Systems (ROS), racing simulators, autonomous driving methods including reactive and deliberative methods; simultaneous localization and mapping (SLAM); path planning and race-line optimization; learning and vision with image classification and obstacle detection. This course is a version of
ECE 306
for graduate students. Credit not given for both
ECE 306
and
ECE 406
Prerequisites:
ECE 108
and (
MATH 205
or
CSE 140
ECE 411
Information Theory
Credits
Introduction to information theory. Topics covered include: development of information measures for discrete and continuous spaces study of discrete-stochastic information courses, derivation of noiseless coding theorems, investigation of discrete and continuous memoryless channels, development of noisy channel coding theorems.
ECE 413
Power Electronics
Credits
Introduction to power semiconductor devices, circuits, and applications. Diodes, thyristors, bipolar and MOS transistors, IGBTs, and other emerging types, and their use in typical power conversion circuits such as rectifiers, buck and boost converters, and dc-dc, dc-ac, and ac-ac inverters and converters. Application examples in motor drives, power supplies and HVDC transmission. This course, a version of
ECE 313
for graduate students, requires research projects and advanced assignments. Credit will not be given for both
ECE 313
and
ECE 413
Prerequisites:
ECE 081
ECE 414
Statistical Decision Making and Machine Learning Theory
Credits
To teach the statistical theory describing the performance of general Machine Learning and Statistical Decision Making approaches. We will not attempt to describe details of specific machine learning algorithms, code those algorithms and test them on real data. Students will learn some needed hypothesis testing theory and estimation theory that is necessary to understand learning theory. Students will learn Probably Approximately Correct learning theory. Credit will not be given for both
ECE 314
and
ECE 414
Prerequisites:
ECE 108
and (
MATH 231
or
MATH 309
ECE 416
VLSI Signal Processing
Credits
The fundamentals of performance-driven VLSI systems for signal processing. Analysis of signal processing algorithms and architectures in terms of VLSI implementation. VLSI design methodology. Includes a design project which requires use of a set of tools installed on SUN workstations for behavioral simulation, structural simulation, circuit simulation, layout, functional simulation, timing and critical path analysis, functional testing, and performance measurement.
ECE 418
INTRODUCTION TO INTERNET OF THINGS
Credits
Basic framework of the Internet of Things (IoT) including both hardware and software, with principles and applications. Principles cover IoT architecture, embedded systems, technology standards, wireless protocols, and device and network cybersecurity. Application aspects include hands-on experiments with IoT devices, power consumption and low-power modes, sensors and actuators, narrowband Radio Frequency (RF) communications, and IoT applications. This course is a version of
ECE 318
for graduate students. Credit will not be given for both
ECE 318
and
ECE 418
ECE 420
Advanced Circuits and Systems
Credits
Review of the fundamentals of Circuits and Systems theory, including the time and frequency domain response of linear time-invariant circuits. Equation formulation for general lumped circuits, including node voltage and loop current analysis. Basic graph theoretic properties of circuits including Tellegen’s Theorem. Discussion of passivity and reciprocity including multiport network properties. State space formulation and solution of general circuits (and systems). Modern filter concepts, including synthesis techniques for active filters and externally linear filters, such as Log Domain filters. Techniques for the analysis of weakly nonlinear systems, as time permits. Must have graduate standing.
Prerequisites:
ECE 125
ECE 421
Introduction to Power Systems
Credits
Power systems engineering relating to generation, transmission, distribution and utilization of electric power. This course introduces basic yet critical concepts of large-scale power systems. Topics include power system modeling, power flow, symmetrical faults, unsymmetrical faults, transient stability, and optimal power flow. This course, a version of
ECE 321
for graduate students, requires research projects and advanced assignments.
ECE 321
and
ECE 421
may not both be taken for credit.
Prerequisites:
ECE 123
ECE 422
Introduction to Photovoltaic Energy Systems
Credits
Basic principles for design, installation, and operation of photovoltaic energy systems. Properties of sunlight and physics of photovoltaic cells. Photovoltaic cells, modules, and arrays. Inverters and other system components. Site assessment. Design and installation of grid-connected and stand-alone PV systems. Systems operation. Maintenance, performance, and economic analysis. Relevant design and simulation tools are introduced. This course, a version of
ECE 321
for graduate students, requires research projects and advanced assignments. Credit not given for both
ECE 322
and
ECE 422
Prerequisites:
ECE 081
ECE 425
Semiconductor Lasers I
Credits
Review of elementary solid-state physics. Relationships between Fermi energy and carrier density and leakage. Introduction to optical waveguiding in simple doubleheterostructures. Density of optical modes, Blackbody radiation and the spontaneous emission factor. Modal gain, modal loss, and confinement factors. Einstein’s approach to gain and spontaneous emission. Periodic structures and the transmission matrix. Ingredients. A phenomenological approach to diode lasers. Mirrors and resonators for diode lasers. Gain and current relations. This course, a version of
ECE 325
for graduate students, requires research projects and advanced assignments. Credit will not be given for both
ECE 325
and
ECE 425
Prerequisites:
ECE 203
ECE 426
Semiconductor Lasers II
Credits
Continuation of Semiconductor Lasers I. Topics covered include: Gain and current relations; dynamic effects; perturbation and coupled-mode theory; dielectric waveguides; and photonic integrated circuits. This course, a version of
ECE 326
for graduate students, requires research projects and advanced assignments. Credit will not be given for both
ECE 326
and
ECE 426
Prerequisites:
ECE 203
ECE 427
Communications & Networking for Smart Grids
Credits
Overview of smart grid electricity systems. Concepts covered include power system background and operations, electricity markets, legacy grid communications, and the smart grid vision and objectives. Additional focus on relevant communications and networking technologies that enable smart grid applications, such as real-time grid monitoring, automated control, demand response, distributed energy systems, microgrids, vehicle-to-grid integration, and smart homes and buildings. This course is a version of
ECE 327
for graduate students. Credit not given for both
ECE 327
and
ECE 427
Prerequisites:
ECE 108
ECE 428 (ECO 428)
Electricity Economics
Credits
Course focuses on the intersection between economics & electricity systems, and market structures available in the electric energy industry. Background provided on basic economic theory applied to power systems to understand operations objectives, pricing & incentives, as well as non-perfect competition situations that arise in the network. Different dispatch optimization problems used in electricity market restructuring, approaches to solving these, and the existence of non-convex markets will be discussed. Credit not given for both ECO/
ECE 328
and ECO/
ECE 428
ECE 429
Power System Modeling and Computation
Credits
A comprehensive study of various computational methods that form the basis of many analytical studies of power systems. Topics include power system modeling, solution of linear systems, systems of nonlinear equations, sparse matrix solution techniques, numerical integration, optimization, and their applications in power system analysis. Students are enabled to make informed decisions in their use of commercial software packages and correctly interpret the results. Matlab is used extensively.
ECE 329
and
ECE 429
may not both be taken for credit.
Prerequisites:
ECE 321
or
ECE 421
ECE 432
Spread Spectrum and CDMA
Credits
Fading and dispersive channel model, direct sequence spread spectrum, frequency hopping spread spectrum, DS-CDMA, FH-CDMA, spread sequences and their properties, multi-user detection, PN code acquisition, wireless communication systems, industrial standards (IS-95, WCDMA, CDMA2000).
ECE 433 (CHE 433, ME 433)
Linear Systems and Control
Credits
This course covers the following topics in linear systems and control theory: review of fundamental concepts in linear algebra, state-space representation of linear systems, linearization, time-variance and linearity properties of systems, impulse response, transfer functions and their state-space representations, solution to LTI and LTV state equations, Jordan form, Lyapunov stability, input-output stability, controllability, stabilizability, observability, detectability, Canonical forms, minimal realizations, introduction to optimal control theory, Linear Quadratic Regulator (LQR), Algebraic Riccati Equation (ARE), frequency domain properties of LQR controllers.
Prerequisites:
ME 343
or
ECE 212
or
CHE 386
ECE 434 (CHE 434, ME 434)
Multivariable Process Control
Credits
A state-of-the-art review of multivariable methods of interest to process control applications. Design techniques examined include loop interaction analysis, frequency domain methods (Inverse Nyquist Array, Characteristic Loci and Singular Value Decomposition) feed forward control, internal model control and dynamic matrix control. Special attention is placed on the interaction of process design and process control. Most of the above methods are used to compare the relative performance of intensive and extensive variable control structures.
Prerequisites:
CHE 433
or
ME 433
or
ECE 433
ECE 435
Error-Correcting Codes
Credits
Error-correcting codes for digital computer and communication systems. Review of modern algebra concentrating on groups and finite fields. Structure and properties of linear and cyclic codes for random or burst error correction covering Hamming, Golay, Reed-Muller, BCH and Reed-Solomon codes. Decoding algorithms and implementation of decoders.
ECE 436 (CHE 436, ME 436)
Systems Identification
Credits
The determination of model parameters from time-history and frequency response data by graphical, deterministic and stochastic methods. Examples and exercises taken from process industries, communications and aerospace testing. Regression, quasilinearization and invariant-imbedding techniques for nonlinear system parameter identification included.
Prerequisites:
ECE 433
or
ME 433
or
ECE 433
ECE 438
Quantum Electronics
Credits
Electromagnetic fields and their quantization. propagation of optical beams in homogeneous and lens-like media. Modulation of optical radiation. Coherent interactions of radiation fields and atomic systems. Introduction to nonlinear optics-second-harmonic generation. Parametric amplification, oscillation, and fluorescence. Third-order optical nonlinearities. This course, a version of
ECE 338
for graduate students, requires research projects and advanced assignments. Credit will not be given for both
ECE 338
and
ECE 438
ECE 440
Introduction to Online and Reinforcement Learning
Credits
Review of probability and random processes, basic reinforcement learning framework, learning from streaming data, actions in response to changing environment through Markov Decision Processes, elements of artificial intelligence. Exploration-Exploitation tradeoffs through bandit problems, and different methods for reinforcement learning including dynamic programming, Monte Carlo methods, temporal difference and Q-learning. Approximate solutions for very large state space systems, policy iteration and actor critic methods, introduction of deep reinforcement learning. Credit will not be given for both
ECE 340
and
ECE 440
Repeat Status:
Course may be repeated.
Prerequisites:
MATH 231
or
MATH 309
ECE 441
Fundamentals of Wireless Communications
Credits
Characterization of mobile radio channels. Wireless information transmission: modulation/demodulation, equalization, diversity combining, coding/decoding, multiple access methods. Overview of cellular concepts and wireless networking. This course, a version of
ECE 341
for graduate students, requires research projects and advanced assignments. Credit will not be given for both
ECE 341
and
ECE 441
Prerequisites:
ECE 342
or
ECE 342
ECE 443
RF Power Amplifiers for Wireless Communications
Credits
Review of linear power amplifier design. Discussion of major nonlinear effects, such as high-efficiency amplifiers modes, matching network design for reduced conduction angle, overdrive and limiting effects, and switching mode amplifiers. Discussion of other nonlinear effects, efficiency enhancement and linearization techniques. Companion course to
ECE 463
ECE 445
Fundamentals of Data Networks
Credits
This course provides analytical foundations in the design and evaluation of data networks. Graphical and dynamical models underlying network design will be discussed with applications in practical networks such as the Internet and Social Media. Key topics covered include queuing, Dynamic Programming, Optimization and Auctions with application in network delay analysis, packet routing, cellular networking, and social media advertising. Background on probability and random processes will be reviewed. Credit will not be given for both
ECE 345
and
ECE 445
Prerequisites:
MATH 231
or
MATH 309
) and
ECE 108
Can be taken Concurrently:
MATH 231
MATH 309
ECE 448
Fundamentals of Photonics
Credits
Concepts of generation, transmission, modulation, and detection of electromagnetic-waves. Paraxial rays and Gaussian beams in uniform media. Wave propagation in integrated waveguides and optical-fibers. Optical-cavity resonators. Light-matter interaction, absorption and amplification of radiation, spontaneous and stimulated-emission. Theory of laser-oscillation and linewidth-narrowing. Wave propagation in anisotropic media. Optical components such as waveplates, optical-couplers and isolators, electro-optic modulators, and photodetectors. Devices with periodic media such as Bragg-reflectors and distributed-feedback lasers. Credit will not be given for both
ECE 348
and
ECE 448
ECE 450
Special Topics
1-3
Credits
Selected topics in electrical and computer engineering not covered in other courses.
Repeat Status:
Course may be repeated.
ECE 451
Physics of Semiconductor Devices
Credits
Crystal structure and space lattices, crystal binding, lattice waves and vibrations, electrons and atoms in crystal lattices. Quantum mechanics and energy band theory, carrier statistics, Boltzmann transport theory, interaction of carriers with scattering centers, electronic and thermal conduction. Magnetic effects. Generation and recombination theory. Application to p-n junctions.
Repeat Status:
Course may be repeated.
Prerequisites:
ECE 126
ECE 454
Turbo Codes and Iterative Decoding
Credits
Capacity-approaching error correcting codes. Soft-in soft-out iterative decoding. Parallel/serial/hybrid concatenated convolutional codes—and turbo-like codes. Iterative decoding algorithms and performance analysis of parallel/serial turbo codes. Low density parity check (LDPC) codes and product codes. Code graph and message passing decoding algorithms. Turbo and LDPC code design and construction. Performance analysis using density evolution and extrinsic information transfer charts. Applications of turbo and LDPC codes.
ECE 455
Theory of Metal Semiconductor and Heterojunction Transistors
Credits
Physics of metal semiconductor and heterojunction field effect transistors (MESFET and HEMT). Theory of semiconductor heterojunctions. Properties of heterojunction bipolar transistors (HBT): Equivalent circuits, applications to microwave amplifiers, oscillators, and switching circuits.
ECE 460
Engineering Project
3-6
Credits
Project work in an area of student and faculty interest. Selection and direction of the project may involve interaction with industry. Consent of department required.
ECE 463
Design of Microwave Solid State Circuits
Credits
Equivalent circuit modeling and characterization of microwave semiconductor devices, principles of impedance matching, noise properties and circuit interaction, introduction to the design of high power and non-linear circuits.
ECE 464
Introduction to Cryptography and Network Security
Credits
Introduction to cryptography, classical cipher systems, cryptanalysis, perfect secrecy and the one time pad, DES and AES, public key cryptography covering systems based on discrete logarithms, the RSA and the knapsack systems, and various applications of cryptography. This graduate version of
ECE 364
requires additional work. May not be taken with
ECE 364
for credit. Must have graduate student status.
ECE 465
VLSI Implementation of Error Control Coding
Credits
Error control coding, finite field arithmetic, encoding and decoding of BCH and Reed-Solomon codes, efficient iterative decoders for convolutional and Turbo codes, message passing and high performance decoders for low-density parity-check codes.
Prerequisites:
ECE 435
ECE 466 (BIOE 466)
Credits
Neural system interfaces for scientific and health applications. Basic properties of neurons, signal detection and stimulation, instrumentation and microfabricated electrode arrays. Fundamentals of peripheral and central neural signals and EEG, and applications such as neural prostheses, implants and brain-computer interfaces. Closed to students who have taken
BIOE 366
ECE 366
, or
BIOE 466
. Students enrolled in the course at the 400-level must complete additional advanced assignments, as defined by the course instructor.
ECE 468 (BIOE 468)
Introduction to Biophotonics and Optical Biomedical Imaging
Credits
Optical principles, techniques, and instruments used in biomedical research and clinical medicine. Fundamental concepts of optical imaging and spectroscopy systems, and details of light-tissue interaction. Commercial devices and instruments, as well as novel optical imaging technologies in development. Closed to students who have taken
BIOE 468
ECE 368
, or
ECE 468
. Students enrolled in the course at the 400-level must complete additional advanced assignments, as defined by the course instructor.
ECE 471
Optical Information Processing
Credits
Introduction to optical information processing and applications. Interference and diffraction of optical waves. 2D optical matched filters that use lenses for Fourier transforms. Methods and devices for modulating light beams for information processing, communications, and optical computing. Construction and application of holograms for optical memory and interconnections. The course is an extension of
ECE 371
for graduate students and it will include research projects and advanced assignments.
Prerequisites:
ECE 108
ECE 472
Optical Networks
Credits
Study the design of optical fiber local, metropolitan, and wide area networks. Topics include: passive and active photonic components for optical switching, tuning, modulation and amplification; optical interconnection switches and buffering; hardware and software architectures for packet switching and wavelength division multiaccess systems. This class is supported with a laboratory. The course is an extension of
ECE 372
for graduate students and it will include research projects and advanced assignments.
Prerequisites:
ECE 081
ECE 473
Smart Grid Operation and Control
Credits
Introduction to smart grids, microgrids and their components, control of microgrids, intro to neural networks and deep learning, deep learning for solving optimization problems in smart grids, machine learning based economic dispatch and optimal power flow, control of distributed energy resources, grid following and grid forming control of renewable energy, data-driven model identification using statistical learning, machine learning based control of distributed energy resources. Graduate version of ECE373. Credit may not be given for both ECE373 and ECE473.
ECE 475
Semiconductor Optoelectronics
Credits
Theory and practical implementation of semiconductor optoelectronic devices. Broad coverage of the fundamentals of the propagation, modulation, generation, and detection of light. Topics include the energy transfer between photons and electron-hole pairs, light emission and absorption, radiative and non-radiative processes, electrical and optical characteristics, carrier diffusion and mobility, light extraction and trapping. Specific devices include laser diodes, light-emitting diodes, electroabsorption modulators, photodetectors, and solar cells. Credit will not be given for both
ECE 375
and
ECE 475
ECE 477
Introduction of Electrical Machines
Credits
Comprehensive review of AC electrical circuits, magnetic circuits, and fundamental electromagnetic principles; modeling, testing, and analysis of single-phase and three-phase transformers; models and operational characteristics of various types of DC machines; introduction to fundamental concepts of AC machines; principles and performance analysis of synchronous generators, synchronous motors, and induction motors. Graduate-level version of
ECE 377
. Credit may not be given to both
ECE 377
and
ECE 477
ECE 485
Heterojunction Materials and Devices
Credits
Material properties of compound semiconductor heterojunctions, quantum wells and superlattices. Strained layer epitaxy and band-gap engineering. Theory and performance of novel devices such as quantum well lasers, resonant tunneling diodes, high electron mobility transistors, and heterojunction bipolar transistors. Complementary to ECE 452.
Prerequisites:
ECE 451
ECE 490
Thesis
1-6
Credits
ECE 491
Research Seminar
1-3
Credits
Regular meetings focused on specific topics related to the research interests of department faculty. Current research will be discussed. Students may be required to present and review relevant publications. Consent of instructor required.
Repeat Status:
Course may be repeated.
ECE 492
Independent Study
1-3
Credits
An intensive study, with report, of a topic in electrical and computer engineering which is not treated in other courses. Consent of instructor required.
Repeat Status:
Course may be repeated.
ECE 493
Solid-State Electronics Seminar
Credits
Discussion of current topics in solid-state electronics. Topics selected depend upon the interests of the staff and students and are allied to the research programs of the Sherman Fairchild Laboratory for Solid State Studies. Student participation via presentation of current research papers and experimental work. Consent of instructor required.
Repeat Status:
Course may be repeated.
ECE 499
Dissertation
1-15
Credits
Repeat Status:
Course may be repeated.
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