This is the list of courses that the department may offer in a given year. See the current course offerings page for courses offered this semester. Not all courses in the catalog are offered every year. Undergraduate students normally take courses in the 100 – 400 level range, and graduate students normally take courses in the 400 – 500 level range.
ECE 115 Introduction to Computing: Programming Autonomous Vehicles
This course is an introductory course in programming and computing concepts for engineering students who have little or no experience in computing and programming and are interested in learning programming in the context of a robotic autonomous vehicle system. Introduction to fundamental programming concepts: control flow, iteration, abstraction, sub-routines, functions, recursion, lists and arrays. This course is tightly integrated with a real robotic platform: an autonomous Unmanned Aerial Vehicle which the students will program and fly in lab as they learn programming. Significant emphasis will be placed on building good debugging skills.
ECE 201 Information Signals (ST)
An introductory overview of electrical systems that process information-carrying signals. Acquisition, distribution, storage, and utilization of common information, such as text, voice, image, and video. Important attributes and characterization of analog and digital signals. Conversion between analog and digital signals. Modeling of information-distributing systems. Introduction to modulation. Limitations of physical information processing systems. Elementary coding for error detecting and correcting. Simple control systems, feedback principle. Three hours of lectures, one three-hour laboratory. Prerequisite: knowledge of elementary calculus
ECE 203 Electronic Circuit Design Analysis and Implementation (ST)
Introduction to circuit analysis and electronics. Passive components and circuits, operational amplifiers, feedback. Resistive networks, Kirchhoff's laws, Thevenin and Norton equivalent circuits. Capacitors and inductors. Switched RL, RC, and RLC circuits. Oscillation. Sinusoidal steady-state analysis, frequency response. Bode diagrams. Electromechanical energy conversion. Three hours of lectures, one three-hour laboratory. Prerequisite: knowledge of freshman physics and elementary calculus.
ECE 206 Contemporary Logic Design (also COS 306) (ST)
Boolean algebra and digital logic gates. Design with two- and multilevel combinational logic. Basic memory elements, latches, flip-flops, SRAM and DRAM cells. Timing methodologies. Synchronous and asynchronous designs. Counters. Finite-state machines. Designs with programmable logic. Basic computer organization. Three lectures, one laboratory. Prerequisite: an introductory programming course, or equivalent programming experience.
ECE 273 Renewable Engergy and Smart Grids (see ENE 273)
ECE 297 and 298 Sophomore Independent Work
Provides an opportunity for a student to concentrate on a state-of-the-art project in electrical and computer engineering. Topics may be selected from suggestions by faculty members or proposed by the students. The final choice must be approved by the faculty advisor. There is no formal reading list; however, a literature search is a normal part of most projects.
ECE 301 Designing Real Systems
This course focuses on the science, engineering, and design of the highly integrated systems that dominate many of today's devices. Analysis of systems, sub-systems, and basic principles will be covered, with an emphasis on hardware-software optimization, sampling and digitization, signal and noise, feedback and control, and communication. Prerequisites: 201 and 203.
ECE 302 Robotic and Autonomous Systems Lab
Comprehensive laboratory-based course in electronic system design and analysis. Covers formal methods for the design and analysis of moderately complex real-world electronic systems. Course is centered around a semester-long design project involving a computer-controlled vehicle designed and constructed by teams of two students. Integrates microprocessors, communications, and control. Three lectures, one laboratory; open laboratory during final month. Prerequisites: 201 and 203.
ECE 304 Electronic Circuits: Devices to ICs
The course will cover topics related to electronic system design through the various layers of abstraction from devices to ICs. The emphasis will be on understanding fundamental system-design tradeoffs, related to the speed, precision, power with intuitive design methods, quantitative performance measures, and practical circuit limitations. The understanding of these fundamental concepts will prepare students for a wide range of advanced topics from circuits and systems for communication to emerging areas of sensing and biomedical electronics. Prerequisites: 201 and 203.
ECE 305 Mathematics for Numerical Computing and Machine Learning (also COS 302, SML 305)
This course provides a comprehensive and practical background for students interested in continuous mathematics for computer science. The goal is to prepare students for higher-level subjects in artificial intelligence, machine learning, computer vision, natural language processing, graphics, and other topics that require numerical computation. This course is intended students who wish to pursue these more advanced topics, but who have not taken (or do not feel comfortable) with university-level multivariable calculus (e.g., MAT 201/203) and probability (e.g., ORF 245 or ORF 309).
ECE 308 Electronic and Photonic Devices (ST)
An examination of what is inside a microchip, how it works, and how it is made. Operating principles of semiconductor devices and their function in circuit applications such as digital gates and analog amplifiers. Devices to include p-n junction diodes, bipolar transistors, MOS capacitors, and field-effect transistors (MOSFET's). Microfabrication technology for semiconductor devices, integrated circuits, photolithography, etching, evaporation, and other thin-film processing. Hands-on integrated circuit microfabrication laboratory for diodes and MOSFET's. Three lectures, one laboratory. Prerequisite: CHM 201 or 203. Corequisite: PHY 102 or 104 or EGR 153.
ECE 341 Solid-State Devices
The physics and technology of solid-state devices. Topics include: p-n junctions and two terminal devices, transistors, silicon controlled rectifiers, field effect devices, silicon vidicon and storage tubes, metal-semiconductor contacts and Schottky barrier devices, microwave devices, junction lasers, liquid crystal devices, and fabrication of integrated circuits. Three hours of lectures. Prerequisite: 308 or the equivalent.
ECE 342 Principles of Quantum Engineering
Fundamental principles of solid-state and optoelectronic device operation. Principles of quantum mechanics (Schroedinger equation, operator and matrix methods) important to a basic understanding of solid-state and quantum electronics. Topics in statistical mechanics, including distribution functions, density of states, Maxwell-Boltzmann, Fermi-Dirac, and Bose-Einstein statistics. Applications to atoms, molecules, lasers, and solids, with special emphasis on semiconductors. Three hours of lectures. Prerequisites: PHY 103/105 and 104/106 or EGR 151/153.
ECE 345 Introduction to Robotics (also MAE 345, COS 346)
Robotics is a rapidly-growing field with applications including unmanned aerial vehicles, autonomous cars, and robotic manipulators. This course will provide an introduction to the basic theoretical and algorithmic principles behind robotic systems. The course will also allow students to get hands-on experience through project-based assignments on quadrotors. In the final project, students will implement a vision-based obstacle avoidance controller for a quadrotor. Topics include motion planning, control, localization, mapping, and vision.
ECE 346 Intelligent Robotic Systems (also COS348, MAE346)
Robotic systems are quickly becoming more capable and adaptable, entering new domains from transportation to healthcare. To operate in dynamic environments, interact with other agents, and accomplish complex tasks, these systems require sophisticated decision-making. This course delves into the core concepts and techniques underpinning modern autonomous robots, including planning under uncertainty, active perception, learning-based control, and multiagent decision-making. Lectures cover the theoretical foundations and the practical component introduces the Robot Operating System (ROS) framework through hands-on assignments with mobile robots. Prerequisite: MAE/ECE 345/COS 346: Introduction to Robotics. Students must have taken this course or its equivalent. Recommended: an introductory course in dynamical systems and/or control theory (ideally, MAE 434; alternatively, ECE 201, MAE 206 or similar) and an introductory course in probability (ORF 309 or similar).
ECE 351 Foundations of Modern Optics
Electromagnetic field theory with emphasis on engineering applications. Review of static fields, Maxwell's equations, wave propagation, reflection and refraction, dielectric and metallic waveguides, fiber optics and practical concepts in lightwave communications systems. Three hours of lectures. Prerequisite: PHY 104/EGR 153.
ECE 364 Machine Learning for Predictive Data Analytics
Machine learning for predictive data analytics; data to insight to decisions; data exploration; information-based learning; similarity-based learning; probability-based learning; error-based learning; evaluation; case studies.
ECE 375 Computer Architecture and Organization (also COS 375)
An introduction to computer architecture and organization. Instruction set design; basic processor implementation techniques; performance measurement; cashes and virtual memory; pipelined processor design; design trade-offs among cost, performance, and complexity. Prerequisite: COS 217.
ECE 368 Introduction to Wireless Communication Systems
Communication systems have become a ubiquitous part of modern life. This course introduces students to the fundamentals of digital communication and wireless systems. Topics include concepts from information, compression, channel, modulation, radio propagation to principles of wireless cellular, and WiFi systems. At the end of the semester, students are expected to gain a deep understanding of the basis of wireless communication systems and the connection between theoretical concepts and real-world systems.
ECE 381 Networks: Friends, Money and Bytes (also COS 381)
This course is oriented around 20 practical questions in the social, economic, and technological networks in our daily lives. How does Google sell ad spaces and rank webpages? How does Netflix recommend movies and Amazon rank products? How do I influence people on Facebook and Twitter? Why doesn't the Internet collapse under congestion, and does it have an Achilles heel? Why does each gigabyte of mobile data cost $10, but Skype is free? How come WiFi is slower at hotspots than at home, and what is inside the cloud of iCloud? In formulating and addressing these questions, we introduce the fundamental concepts behind the networking industry.
ECE 382 Statistical Signal Processing
A wide spectrum of engineering applications require efficient procedures to describe, process, analyze, and infer the signals/data of interest, which are often accomplished by imposing proper statistical models on the objects under consideration. This course introduces the fundamental statistical principles and methods that play a central role in modern signal and information processing. Specific topics include random processes, linear regression and estimation, hypothesis testing and detection, and shrinkage methods. Prerequisites: Linear Algebra and ORF 309.
ECE 396 Introduction to Quantum Computing (also COS 396)
This course will introduce the matrix form of quantum mechanics and discuss the concepts underlying the theory of quantum information. Some of the important algorithms will be discussed, as well as physical systems which have been suggested for quantum computing. Three lectures. Prerequisite: Linear algebra at the level of MAT 202, 204, 217, or the equivalent.
ECE 397 and 398 Junior Independent Work
Provides an opportunity for a student to concentrate on a "state-of-the-art" project in electrical and computer engineering. Topics may be selected from suggestions by faculty members or proposed by the students. The final choice must be approved by the faculty advisor. There is no formal reading list; however, a literature search is a normal part of most projects.
ECE 404/504 Mixed-Signal Circuits and Systems
Discuss design and simulation methodologies for realizing robust analog CMOS circuits implementing major building blocks in A/D conversion. With attention to design specifications, a comprehensive study of single-ended and differential op-amp topologies will be covered with an emphasis on: feedback and stability; linear and non-linear settling; distortion; noise; and voltage swing. Conclude with swtiched-capacitor circuits exploring impact of non-linearity and noise in sampled systems. Design projects using circuit simulators reinforce theoretical concepts. Prerequisite: 304.
ECE 411 Sequential Division Analytics and Modeling (see ORF 411)
ECE 431 Solar Energy Conversion (also MAE 431/ENV 431/EGR 431/ENE 431)
Principles, designs, and economics of solar conversion systems. Quantity and availability of solar energy. Physics and chemistry of solar energy conversion: solar optics; quantum processes; optical excitation; and transport of excitations, electronic, and ionic charge. Methods for conversion: photovoltaics; photoelectrochemistry; photocatalysis; photosynthesis; and solar thermal conversion. Energy collection, transport and storage. Economics: life cycle costing; and societal value of renewable energy. Three one-hour lectures, one preceptorial. Prerequisites: MAT 104, PHY 104 or EGR 153, and CHM 207.
ECE 432 Information Security (also COS 432)
How to secure computing systems, communications, and users. Basic cryptography; private and authenticated communication; sofware security; malware; operating system protection; network security; web security; physical security; cryptocurrencies and blockchains; privacy and anonymity; usable security; economics of security; ethics of security; legal and policy issues. Prerequisites: COS 217 and 226.
ECE 434 Machine Learning Theory (also COS 434)
The course covers basic theories of modern machine learning: 1. statistical learning theory: generalization, uniform convergence, Rademacher complexity, VC theory, reproducing Hilbert kernel space and their applications on simple classification/regression models; 2. optimization theory: gradient descent, stochastic gradient descent and their convergence analyses for convex functions, nonconvex functions 3. deep learning theory: basic approximation, optimization and generalization results for deep neural networks; 4. reinforcement learning theory: MDP, Bellman equations, planning, and sample complexity results for value iteration/Q-learning.
ECE 435/535 Machine Learning and Pattern Recognition
The course is an introduction to the theoretical foundations of machine learning and pattern recognition. A variety of classical and recent results in machine learning and statistical pattern classification are discussed. Topics include Bayesian classification, regression, regularization, maximum margin classification, kernels, neural networks and stochastic approximation.
ECE 441 Solid-State Physics I (also ENE 441)
An introduction to the properties of solids. Theory of free electrons--classical and quantum. Crystal structure and methods of determination. Electron energy levels in a crystal: weak potential and tight-binding limits. Classification of solids--metals, semiconductors, and insulators. Types of bonding and cohesion in crystals. Lattice dynamics, phonon spectra, and thermal properties of harmonic crystals. Three hours of lectures. Prerequisite: 342, or PHY 208 and 305, or equivalent.
ECE 442 Solid-State Physics II
Electronic structure of solids. Electron dynamics and transport. Semiconductors and impurity states. Surfaces and interfaces. Dielectric properties of insulators. Electron-electron, electron-phonon, and phonon-phonon interactions. Anharmonic effects in crystals. Magnetism. Superconductivity. Alloys. Three hours of lectures. Prerequisites: 441 or equivalent.
ECE 449/549 Micro-Nano Fabrication and Thin Film Processing (also MSE 449)
This course will investigate the technology and underlying science of micro-and nano-fabrication, which are the methods used to build billions of electronic and optoelectronic devices on a chip, as well as general small sensors and actuators generally referred to as micro-electromechanical systems (MEMS). The general approach involves deposition modification, and patterning of layers less than one-micrometer thick, hence the generic term 'thin-film' processing. Topics to be covered film deposition and growth via physical and chemical vapor deposition, photolithography, pattern transfer, plasma-processing, ion-implantation, and vacuum science.
ECE 452 Biomedical Imaging
This course gives a general introduction to biological and biomedical imaging. Topics covered include basic imaging theory, microscopy, tomography, and imaging through tissue. Both physical and computational imaging will be covered, across a variety of different modalities (including visible light, x-ray, MRI, and ultrasound). The gaps between current technology and limits suggested by information theory will be discussed.
ECE 453 Optical and Quantum Electronics
Electromagnetic waves. Gaussian beams. Optical resonators. Interaction of light and matter. Lasers. Mode locking and Q-switching in lasers. Three hours of lectures. Prerequisites: 351 or PHY 304 or permission of instructor.
ECE 455 Optical and Photonic Systems for Environmental Sensing
This class will teach you about optical and photonic sensing technologies and their applications to environmental monitoring. The course will contain elements of atmospheric science and Earth observation, fundamentals of optics, photonics and laser physics, as well as a survey of modern optical and spectroscopic sensing applications. In this course students will be asked to prepare two oral presentations and there will be three laboratory assignments focused on fundamentals of optical sensing.
ECE 456 Quantum Optics (also PHY456)
Semiclassical field theory of light-matter interactions. Quantum theory of light, vacuum fluctuations and photons. Quantum states and coherence properties of the EM field, photon counting and interferometry. Quantum theory of light-matter interactions, Jaynes-Cummigns (JC) model. Physical realizations of JC model, case study:circuit QED. Quantum theory of damping. Resonance fluorescence. Coupled quantum non-linear systems. Prerequisite: 453.
ECE 457 Experimental Methods in Quantum Computing
This course aims to introduce students to the basics of experimental quantum information processing. Students will gain hands-on experience with several qubit platforms, including single photons, nuclear spins (NMR), electron spins (NV centers in diamond), and superconducting qubits. Additionally, students will learn data analysis and signal processing techniques relevant for a wide range of quantum computing platforms. Prerequisite: Quantum mechanics (PHY 305 and/or ECE 342). ECE/COS 396 is recommended but not required.
ECE 458/558 Photonics and Light Wave Communications
Introduction to fiber-optic communication systems. Optical detectors and receivers. Design and performance of direct detection systems. Coherent light wave systems. Multichannel WDM communication systems. Optical amplifiers. Soliton communication systems. Three hours of lectures.
ECE 461 Design with Nanotechnologies
Introduction to nanotechnologies; threshold logic/majority logic and their applications to RTDs, QCA and SETs; nanowire based crossbars and PLAs; carbon nanotube based circuits; double-gate CMOS-based circuits; reversible logic for quantum computing; non-volatile memory; nanopipelining; testing; and defect tolerance. Two 90-minute lectures. Prerequisite: ELE 203 and 206.
ECE 462/562 Design of Very Large-Scale Integrated (VLSI) Systems (also COS 462)
The implementation of digital systems using integrated circuit technology. Emphasis on structured design methodologies for VLSI systems. Topics include: design rules for metal oxide semiconductor (MOS) integrated circuits, implementation of common digital components, tools for computer-aided design, novel architectures for VLSI systems. Three hours of lectures. Prerequisite: 203 and 206.
ECE 463 Wireless Networks (see COS 463)
ECE 464 Embedded Computing
Introduction to embedded computing, cyberphysical systems and Internet-of-Things: basic concepts; reliability, availability, power/energy consumption, security. Finite-state machines. Sensors and actuators. Embedded processors. Performance/power analysis. Real-time systems. System-on-chip architectures. Hardware-software co-design. High-level synthesis. Low-power embedded system design. Prerequisite: 206.
ECE 469 Human-Computer Interface Technology (see COS 436)
ECE 472 Architecture for Secure Computers and Smartphones
We study how to design secure processors, cashes and systems for secure computers and smartphones. Topics include hardware-enhanced secure execution environments, secure cache architectures resilient to side and covert channel attacks, new processor designs for defeating speculative and timing attacks, solving security problems using machine/deep learning, smartphone security architecture, designing a deep learning engine for smartphone security and attacks on deep learning systems. The goal is to train computer architects to design secure computers, and software/security students to understand the importance of hardware in a secure system.
ECE 475/575 Computer Architecture (also COS 475)
An in-depth study of the fundamentals of modern processor and system design. Students will develop a strong practical and theoretical background in the technical and economic issues that govern the design of computer architectures and implementations. The course will emphasize the skills required to design and evaluate current and future systems. Three hours of lectures. Prerequisites: 206, 375.
ECE 477 Kernel Based Machine Learning
With foundation built upon statistical and algebraic learning theory, this course offers an in-depth learning experience on machine learning for (big) data analysis for senior and graduate students in electrical and computer engineering, computer science, and applied statistics - with some exposure to algebra and statistics. It covers various kernel-based unsupervised and supervised learning models and provides an integrated understanding of the mathematical theory and their potential applications. With the accompanied software learning laboratories. It also demonstrates how kernel learning models work for pattern recognition and data analysis.
ECE 480 fMRI Decoding: Reading Minds Using Brain Scans (also NEU 480, PSY 480)
How can we decode what people are thinking by looking at their brain scans? Over the past several years, researchers have started to address this question by applying sophisticated pattern-classification algorithms to patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. In lectures, students will learn about cutting-edge techniques for finding meaningful patterns in large, noisy datasets; in weekly computer labs, students will use these techniques to gain insight into fMRI datasets.
ECE 481/581 Principles Power Electronics (Also ENE 481)
Power electronics circuits are critical building blocks in a wide range of applications, ranging from mW-scale portable devices, W-scale telecom servers, kW-scale motor drives, to MW-scale solar farms. This course is a design-oriented course and will present fundamental principles of power electronics. Topics include: 1) circuit elements;2) circuit topology; 3) system modeling and control; 4) design methods and practical techniques. Numerous design examples will be presented in the class, such as solar inverters, data center power supplies, radio-frequency power amplifiers, and wireless power transfer systems. Prerequisite 203. 308 recommended only.
ECE 482 Digital Signal Processing
The lectures will cover: (1) Basic principles of digital signal processing. (2) Design of digital filters. (3) Fourier analysis and the fast Fourier transform. (4) Roundoff errors in digital signal processing. (5) Applications of digital signal processing.
ECE 486 Transmission and Compression of Information (also APC 486)
Introduction to digital communication systems and networks, introductory information and coding theory, digital modulation, layered architecture concept of networks, introductory traffic and queuing theory, local area networks and media access control, error control in networks, switching and multiplexing, ATM (asynchronous transfer mode) in B-ISDN (broadband integrated services digital networks). Three hours of lectures. Prerequisites: ORF 309.
ECE 488 Image Processing
Introduction to the basic theory and techniques of two- and three-dimensional image processing. Topics include image perception, 2-D image transforms, enhancement, restoration, compression, tomography and image understanding. Applications to HDTV, machine vision, and medical imaging, etc. Three hours of lectures, one laboratory.
ECE 491 High-Tech Entrepreneurship (also EGR 491/ORF 491)
Designed for seniors in the sciences and engineering who are interested in starting a high-tech company early in their careers or who want to join emerging technology companies after graduation. The course is open to any student with a strong background in technology who is interested in launching new enterprises. Two 90-minute lectures.
ECE 497 and 498 Senior Independent Work
Provides an opportunity for a student to concentrate on a "state-of-the-art" project in electrical and computer engineering. A student may propose a topic and find a faculty member willing to supervise the work. Or the student may select a topic from lists of projects obtained from faculty and off-campus industrial researchers, subject to the consent of a project advisor. There is no formal reading list for the course; however, a literature search is a normal part of most projects.
ECE 501/EGR 501 Responsible Conduct in Research
This course educates the graduate student of engineering in the responsible conduct of research. The lectures provide theoretical background information as well as case studies about ethics in day-to-day research situations, in publishing and peer-review, in student-advisor relationships, in collaborative research, as well as in the big picture and considerations of long-term impact. The students are provided with resources to consult in ethical questions. In small-group discussions in departmental and research field-specific precepts, the theoretical concepts are made relevant to the individual students situations.
ECE 513/MSE 531 Introduction to Nano/Microfabrication
Introduces to students the basic technologies and knowledge of nano/microfabrication, and give them hands-on experiences in making nano/microstructures and handling sophisticated equipment. The course consists of four one-hour lectures (one per week), seven three-hour labs (one lab per week), and three experiments. Each student begins with a bare silicon wafer and ends with micro-structures consisting of resistors, capacitors, diodes, and transistors. Students learn and perform wafer cleaning, thermal oxidation of thin films, dopant diffusion, photolithography, chemical etching, metal thin-film evaporation, and related.
ECE 511 Quantum Mechanics with Applications
This course covers the principles of quantum mechanics, including applications of relevance to students in applied physics, materials science and engineering. Topics include the concept of Hilbert Spaces, Schrodinger and Heisenberg Representations, Bound State and scattering problems in one, two and three dimensions, consequences of symmetry, Angular momentum algebra, Approximation methods for stationary states, Many-body systems, Quantum statistics and applications in solid state and quantum optics. Time dependent Perturbation Theory and/or Second Quantization and Electromagnetic Field are covered if time permits.
ECE 514 Extramural Research Internship
Full-time research internship at a host institution, to perform scholarly research relevant to student's dissertation work. Research objectives will be determined by advisor in conjunction with outside host. A mid-semester progress review and a final paper are required. Enrollment limited to post-generals students for up to two semesters. Special rules apply to international students regarding CPT/OPT use. Students may register by application only.
ECE 515 Extramural Summer Project
Summer research project designed in conjuction with the student's advisor and an industrial, NGO, or government sponsor, that will provide practical experience relevant to the student's research area. Start date no earlier than June 1. A research project and sponsor's evaluation are required.
ECE 518 and 519 Seminar in Information Sciences and Systems
A forum of graduate students, staff, and distinguished outside speakers presenting their recent research in signal processing, communication and information theory, decision and control, and systems theory. Attendance by ISS students is required.
ECE 520 Optimization and Optimal Control
A study of optimization theory using a vector space approach. Topics include a review of finite dimensional linear spaces and a discussion of extensions to infinite dimensional (function) spaces; operators and functional analysis; minimum norm problems; duality, convexity, and constrained optimization problems; and Lagrange multiplier theory and applications to optimal control, including the maximum principle. Emphasis is on theoretical foundations as interpreted geometrically through the vector space setting.
ECE 521/MAE 547 Linear System Theory
This course covers the fundamentals of linear system theory. Various topics important for further study in dynamic systems, control and communication and signal processing are presented.
ECE 523/MAE 548 Nonlinear System Theory
A study of the mathematical techniques found useful in the analysis and design of nonlinear systems. Topics include stability and qualitative behavior of differential equations, functional analysis and input/output behavior of systems, and "modern'' nonlinear system theory, which uses both geometric and algebraic techniques. Prerequisite: 521.
ECE 524 Theory of Statistical Inference
Logical foundations of estimation from classical Bayesian and decision theory viewpoints. It gives an introduction to statistical hypothesis testing. It examines parametric and non-parametric approaches and large sample theory.
ECE 525 Random Processes in Information Systems
Fundamentals of probability and random processes and their applications to information sciences and systems. The course examines sequences of random variables and convergence; stationarity and ergodicity; second-order properties and estimation; Poisson and renewal processes; and Markov processes.
ECE 526 Digital Communications and Systems
Digital communications and data transmission. Topics include source coding, signal encoding, representation, and quantization; methods of modulation, synchronization, and transmission; optimum demodulation techniques; and communication through band-limited and random channels.
ECE 527 Selected Topics in Signal Processing
Topics of current interest on digital signal processing algorithms and their implementation, including floating point arithmetic roundoff errors, fast transform algorithms, multirate and multidimensional signal processing, spectral estimation, and adaptive signal processing. Prerequisites: 482 and 525 or the equivalent.
ECE 528 Information Theory
An exploration of the Shannon theory of information, covering noiseless source coding theory of ergodic sources and channel coding theorems, including channels with memory, multiple-access, and Gaussian channels.
ECE 529 Theory/Phys Foundations/Random Processes
A systematic treatment of the mathematical properties of stochastic processes. The course explores fundamental concepts and general properties; convergence, second-order processes, and processes of orthogonal increments; and Wiener theory. It examines Brownian motion and stochastic integrals and processes with independent increments. Markov processes and diffusion equations and stochastic differential equations are studied. There are applications in detection, estimation, and stochastic control. Prerequisite: 485 or 525 or the equivalent.
ECE 530 Theory of Detection and Estimation
Hypothesis testing; detection and estimation of signals in noise; detection of signals with unknown parameters; prediction and filtering of stationary time series; detection of stochastic signals; and nonparametric and robust techniques. Prerequisite: 525 or the equivalent.
ECE 531 Communication Networks
Modeling and analysis of high-speed communication networks. Topics include M/M/1, M/G/1, G/M/m, and G/G/1 queues; queueing networks and loss networks; network architectures and protocols; media access control, multiplexing, and switching; resource allocation and congestion control; local area networks, TCP/IP Protocol in Internet, and B-ISDN ATM networks. Prerequisites: 525 or the equivalent and a familiarity with topics in 486 is desirable.
ECE 532 Adaptive Systems
The theory and application of adaptive systems in communications and control. Course examines learning techniques and related models; the role of sufficient statistics; recursive and empirical Bayes procedures; and convergence properties. Simultaneous detection and estimation is studied. Topics discussed include intersymbol interference and channel equalization, model-reference adaptive systems, multipath communication, adaptive data compression, decision-directed receivers, adaptive filtering, and arrays. Prerequisite: 525 or the equivalent.
ECE 533 Multiuser Communication Theory
Communication channels shared by several users, with an emphasis on applications in wireless communication. Time-division and frequency-division multiplexing, random-access communications, and code-division multiple-access (CDMA) are studied. A primary focus of the course is the analysis and design of multiuser detection for interference suppression in CDMA. Prerequisites: 486 and 525 or equivalent.
ECE 534 Fiber-Optic Communication Systems
Guided wave optical transmission in fibers and planar waveguides; fiber types and their characteristics, such as loss and bandwidth; the performance of light-emitting diodes and semiconductor lasers in fiber-optic systems; modulation techniques; the principles of direct, homodyne, and heterodyne photodetection; noise in optical receivers, including dark current, random carrier multiplication noise, thermal noise, and quantum noise; and system design and performance. Examples of lightwave communication systems are given, including long-haul transmission, fiber-optic local area networks, photonic switching, and VLSI optical micro-area networks.
ECE 535 Machine Learning and Pattern Recognition
An introduction to the theoretical foundations of machine learning and pattern recognition. Topics include Bayesian pattern classification; parametric methods; nearest neighbor classification; Kernel methods; density estimation; VC theory; neural networks; stochastic approximation. Prerequisites: ELE525 or the permission of the instructor.
ECE 538 and 539 Special Topics in Information Sciences and Systems
Advanced studies in selected areas in signal processing, communication and information theory, decision and control, and system theory. Emphasis on recent developments and current literature. Content varies from year to year according to the instructor's and students' interests.
ECE 540 Organic Materials for Photonics & Electronics
An introduction to organic materials with application to active electronic and photonic devices. Basic concepts and terminology in organic materials, and electronic and optical structure-property relationships are discussed. Charge transport, light emission and photoinduced charge transfer are examined. Finally, archetype organic devices as light emitting diodes, photodetectors and transistors are described.
ECE 541/MSE 510 Electronic Materials
The science and technology of materials used in electronics and optoelectronics, with varying emphasis. Subjects include the growth of crystals and of thin films, vacuum technology, phase diagrams, defects and atomic diffusion in semiconductors, techniques for analyzing electronic materials, amorphous silicon, and materials for large-area electronics, displays, and solar cells.
ECE 542 Solid State Physics II
This is a second-semester course with an emphasis on topics of interest to applied physicists and material scientists (e.g., semiconductors, optical properties and dielectrics.) It builds upon the material covered in ELE 441 and extends it to multiple areas. These include electronic structure of solids, electron dynamics and transport, semiconductors and impurity states, electron-electron, electron-phonon, and phonon-phonon interactions, anharmonic effects in crystals, dielectric properties of insulators, magnetism, superconductivity. Prerequisites of ELE 441 or PHY 405 or permission of instructor.
ECE 544 Physics & Technology of Low-Dimensional Electronic Structures
A broad overview of materials science and physics of low-dimensional electronic structures will be presented. Emphasis is on the fabrication and physics of high-mobility carrier systems in modulation-doped structures. Examples include two-dimensional, one-dimensional (quantum wire), and zero-dimensional (quantum dot) systems.
ECE 545 Electronic Devices
The physics and technology of electronic devices; junctions, junction transistors, and field-effect transistors; and MOS; and integrated circuits, and special microwave devices.
ECE 546 Optical Properties of Solids
Classical and quantum mechanical theories for absorption and dispersion. The optical properties are derived from knowledge of electronic band structure of solids, including excitons and effects of external perturbations; the influence of doping, disorder, and reduced dimensionality; bulk and surface polaritons; nonlinear optical processes, and transient and irreversible phenomena. An overview of major measurement techniques is included.
ECE 547 and 548 Selected Topics in Solid-State Electronics
One or more advanced topics in solid-state electronics. Contents vary from year to year. Recent topics have included: electronic properties of doped semiconductors, physics and technology of nanostructures, and organic materials for optical and electronic device application.
ECE 549/MSE 533 Physics and Technology of VLSI
The phenomena encountered in the fabrication of VLSI integrated circuits and the operation of VLSI devices. Processing topics include ion implantation and the role of point defects on oxidation and diffusion. Device topics include scaling theories and submicron MOS and bipolar device design. The course examines computer simulation for both devices and processes; as well as speed-power products and fundamental limits in VLSI. Prerequisites: knowledge of I.C. fabrication techniques and 545 or the equivalent.
ECE 551 Theory and Application of Photonic Devices
A foundation in the principle of operation of semiconductor-based photonic devices. Topics include how system requirements have an impact on device design, semiconductor laser diode and photodiode physics, modulators, and optoelectronic- and photonic-integrated circuits.
ECE 552 Ultrafast and Quantum Optics
Fundamental principles and applications of ultrafast pulse generation, propagation, and detection. The aspects of quantum optics are covered, including coherent states, squeezed states, and quantum noise. The emphasis is placed on practical engineering applications. The goal of the course is to develop a basis for performing research on ultrafast optical phenomena, quantum measurement, and all-optical signal processing.
ECE 553/MSE 553 Nonlinear Optics
An introduction to nonlinear optics, second-harmonic generation, parametric amplification and oscillation, electrooptic effects, third-order nonlinearities, phase-conjugate optics, photorefractive materials, and solitons.
ECE 563 Electronic Design Automation
Case studies in electronic design automation. Focus on fundamental techniques with applications in multiple problems. Current topics include two-level logic minimization, Boolean function representation and manipulation, technology mapping for logic circuits, floor planning, cell placement and routing, timing verification, behavioral synthesis. Work includes research paper presentations, assignments and a final project.
ECE 567/PHY 567 Advanced Solid-State Electron Physics
Electron localization in disordered structures - Anderson model and scaling theory of localization; correlated electron systems - Hubbard model, Mott transition; metal-insulator transitions in correlated and disordered materials; quantum Hall effect - integer and fractional; and quantum phase transitions.
ECE 568 Implementations of Quantum Information
Course begins with an overview of DiVincenzo criteria for physical implementation of algorithms, then moves to consideration of leading contenders for a physical system, including superconducting qubits, electron spins in semiconductors and on liquid helium, and ion-trap-based quantum computers. A variety of possible quantum architectures will be considered. Weekly problem sets. Knowledge of quantum mechanics at the undergraduate level will be assumed.
ECE 570 VLSI Array Processors
Design of VLSI arrays for handling extremely stringent real-time processing for signal/image processing and scientific computing; vertically integrated VLSI system design methodology covering technology constraints, algorithm analyses, parallelism extractions, architecture design, system development, and application understanding; and VLSI architectures, mapping algorithms to arrays, systolic array design, and wavefront array design.
ECE 571 Digital Neurocomputing
Various fundamental aspects of neurocomputing, including theory, modeling, algorithms, architectures, and applications. The course introduces various working network models and the corresponding learning algorithms. It then derives a unification of existing neural nets and basic building blocks of neural computers. The course explores the important future prospects on neural modeling and the potential impacts on conventional algorithm/architecture design as well as promising applications to various image/vision processing and pattern recognition problems.
ECE 572 Processor Architectures for New Paradigms
Advanced instruction-set architecture, micro-architecture, and memory architecture for emerging areas of digital information processing. Algorithm, arithmetic, and architecture techniques for accelerating multimedia information processing and secure information processing with programmable processors. Topics may include: optimal media processors for internet information appliances, and cryptography support for electronic commerce, extranets, and intellectual property protection.
ECE 573/CBE 573 Cellular and Biochemical Computing Systems
A discussion of computational issues in modeling cellular systems and the engineering of synthetic biochemical computing systems. Topics include modeling of genetic regulatory networks using continuous and stochastic methods, construction of synthetic gene networks, metabolic networks, signal transduction pathways, cell-to-cell signaling, molecular and DNA computing, molecular self-assembly, directed molecular evolution, transcriptional and translational regulation, oscillation and circadian clocks, cell differentiation and pattern formation, chemotaxis, molecular switches and molecular electronics, theory of chemical computation.
ECE 579/COS 579 Pervasive Information Systems
Devices and systems that provide information anywhere, anytime. Goals of pervasive information: business, entertainment, government, etc. Components of pervasive information systems: low power electronics, audio/video, networking, etc. Human/computer interaction. Geographically distributed systems.
ECE 580/COS 580 Advanced Topics in Computer Engineering
Selected research topics in computer engineering. Emphasis is on new results and emerging areas. (More detailed outlines are contained in the booklet Course Outlines, issued by the department each year.)
ECE 591 High Tech Entrepreneurship
A course designed for graduate students in the sciences and engineering, particularly those in the masters of engineering program, who are interested in starting up high tech companies early in their careers or who want to join as key contributors new emerging technology companies after graduation. Class sessions are with the undergraduate students enrolled in ELE491. Graduate students will be required to meet and participate in four 90-minute seminars, with special readings and assignments, to address in more detail the techniques for analyzing technologies for commercial feasibility and developing new products that create commercial success
ECE 597 and 598 Electrical and Computer Engineering Master's Project
Under the direction of a faculty member, each student carries out a master's-level project and presents their results. For M. Eng. student, 597, fall term; 598 spring term.