118 courses with the subject ECE, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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.
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.
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
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
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
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)
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
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
Fundamentals of analysis of data obtained via common biomedical measurement techniques, including electroencephalography, electrocardiogram, and optical and mechanical methods. Introduction to filters, removal of noise and artifacts, feature extraction, clustering, and classification. Coverage of common tools and algorithms and application of programming for diagnosis. Students cannot receive credit for both this course and BIOC 213. Prerequisites: MATH 205 and PHY 021
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
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)
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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)
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
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
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
Selected topics in the field of electrical and computer engineering not included in other courses. Repeat Status: Course may be repeated.
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
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
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 includes assignments built upon multiple EDA tools that are used in industry for the design of chips (including simulators, synthesizers, and those used for verification). Prerequisites: ECE 033
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.
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
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
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
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
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
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
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
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
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.
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
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
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.
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.
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
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)
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.
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
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)
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.
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.
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
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
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
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
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
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
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.
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
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).
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
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
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.
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
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.
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
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
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. Credit will not be given for both ECE 342 and ECE 442.
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.
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
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.
Selected topics in electrical and computer engineering not covered in other courses. Repeat Status: Course may be repeated.
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
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.
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.
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.
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.
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.
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
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.
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
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
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.
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.
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.
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
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.
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.
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.
Repeat Status: Course may be repeated.
Source: Lehigh University's catalog, linked per course · table learning_unit · CourseShelf publish 59
