Courses

Graduate Catalogs by Year:

2020-2021

2016-2017

2015-2016

2014-2015

2013-2014

2012-2013


The following graduate level courses are offered in the Klipsch of School of Electrical and Computer Engineering.  Courses in grEEn denote graduate core courses and courses in red denote graduate breadth courses.  Note that graduate core courses are offered at least once per year while other courses are offered may be offered less frequently. 

EE 501 Research Topics in Electrical and Computer Engineering
Ethics and methods of engineering research; contemporary research topics in electrical and computer engineering.


E E 510. Introduction to Analog and Digital VLSI
Introduction to analog and digital VLSI circuits implemented in CMOS technology. Design of differential amplifiers, opamps, CMOS logic, flip-flops, and adders. Introduction to VLSI fabrication process. Recommended foundation: E E 212 and E E 317 Crosslisted with: E E 480.

 

EE 512 ASIC Design
This course provides students with experiential knowledge of modern application specific integrated circuits. Topics include ASIC packaging and testing, I/O pads and ESD, Verilog programming and simulation, FPGA verification, Register-transfer level synthesis, timing and area optimization, floorplanning and routing, digital interfaces, full custom and standard cell design, post-layout simulation, and PCB schematics and layout. Recommended foundation: E E 480. Crosslisted with: E E 412.

 

EE 515 Electromagnetic Theory I
Electromagnetic theory of time-harmonic fields in rectangular, cylindrical and spherical coordinates with applications to guided waves and radiated waves. Induction and equivalence theorems, perturbational and variational principles applied to engineering problems in electromagnetics. Recommended foundation: E E 340.


EE 516 Electromagnetic Theory II

Continuation of EE 515.

EE 519 RF Microelectronics
Knowledge of modern Radio Frequency CMOS integrated circuits, Basic Concepts in RF Design, Communication Concepts, Transceiver Architectures, Low Noise Amplifiers, Mixers, Passive Device in RF Designs, Oscillators, Phase-Locked Loops, Frequency Synthesizers, Power Amplifiers, and State-of-the-art RF systems and applications.
Prerequisite(s): E E 485 or E E 523.

EE 520 A/D and D/A Converter Design
Practical design of integrated data converters in CMOS/BJT technologies, OP-AMPS, comparators, sample and holds, MOS switches, element mismatches. Nyquist rate converter architectures: flash, successive approximation, charge redistribution, algorithmic, two step, folding, interpolating, pipelined, delta-sigma converters.
Prerequisite(s): EE 523.


EE 521. Microwave Engineering

Techniques for microwave measurements and communication system design, including transmission lines, waveguides, and components. Microwave network analysis and active device design. Recommended foundation: E E 340. Crosslisted with: E E 453.


EE 522 Advanced Analog VLSI Design
Design of high-peformance operational amplifiers; class-AB, rail-to-rail, low-voltage, high-bandwidth, fully-differential. Design of linear operational transconductance amplifiers, high-frequency integrated filters, four-quadrant multipliers, and switched-capacitor circuits.
Prerequisite(s): EE 523.


EE 523 Analog VLSI Design
Analysis, design, simulation, layout and verification of CMOS analog building blocks, including references, opamps, switches and comparators. Teams implement a complex analog IC. Recommended foundation: E E 320 and E E 480. Crosslisted with: E E 485.

EE 528 Fundamentals of Photonics
Ray, wave and guided optics, lasers and thermal sources, radiometry, photon detection and signal-to-noise ratio. Elements of photonic crystals, polarization, acousto-optics, electro-optics, and optical nanostructures. Taught with E E 478 with differentiated assignments for graduate students. Recommended foundation: Crosslisted with: PHYS 528.
Prerequisite(s): (PHYS 1320G or PHYS 2120) and E E 473/PHYS 473.


EE 529 Lasers and Applications
Laser operating principles, characteristics, construction and applications. Beam propagation in free space and fibers. Laser diode construction and characteristics. Hands-on laboratory. Recommended foundation: E E 351 or PHYS 461. Taught with: E E 479 with differentiated assignments for graduate students. Crosslisted with: PHYS 529


EE 532 Dynamics of Power Systems
Transient and dynamic stability of power systems; synchronous machine modeling and dynamics; prediction and stabilization of system oscillations. Recommended foundation: E E 493.

EE 534 Power System Relaying
Fundamental relay operating principles and characteristics. Current, voltage, directional, differential relays; distance relays; pilot relaying schemes. Standard protective schemes for system protection. Operating principles and overview of digital relays. Recommended foundation: E E 493.


EE 537 Power Electronics
Basic principles of power electronics and its applications to power supplies, electric machine control, and power systems. Recommended foundation: E E 325, E E 317, and E E 333. Crosslisted with: E E 432.


EE 540 Photovoltaic Devices and Systems
Technical concepts of photovoltaics, with primary focus on solar cell technology. Solar cell device level operation, packaging, and manufacturing. Design of photovoltaic systems for stand-alone or grid-tied operation. Business-case analysis using real-life scenarios of photovoltaic system solutions. Recommended foundation: E E 317. Crosslisted with: E E 440.


EE 541 Antennas and Radiation
Basic antenna analysis and design. Fundamental antenna concepts and radiation integrals. Study of wire antennas, aperture antennas, arrays, reflectors, and broadband antennas. Recommended foundation is E E 340. Crosslisted with: E E 454.


EE 542 Power Systems II
Analysis of a power system in the steady-state. Includes the development of models and analysis procedures for major power system components and for power networks. Recommended foundation: E E 333. Crosslisted with: E E 431.



EE 543 Power Systems III
Analysis of a power system under abnormal operating conditions. Topics include symmetrical three-phase faults, theory of symmetrical components, unsymmetrical faults, system protection, and power system stability. Recommended foundation: E E 431. Crosslisted with: E E 493.


EE 544 Distribution Systems
Concepts and techniques associated with the design and operation of electrical distribution systems. Recommended foundation: E E 542 and E E 543.


EE 545 Digital Signal Processing II
Non-ideal sampling and reconstruction, oversampling and noise shaping in A/D and D/A, finite word length effects, random signals, spectral analysis, multirate filter banks and wavelets, and applications. Recommended foundation: E E 395.


EE 546 Introduction to Smart Grid
The course will serve as an introduction to the technologies and design strategies associated with the Smart Grid. The emphasis will be on the development of communications, energy delivery, coordination mechanisms, and management tools to monitor transmission and distribution networks. Crosslisted with: E E 426 and C S 514.


EE 548 Introduction to Radar
Basic concepts of radar. Radar equation; detection theory, AM, FM, and CW radars. Analysis of tracking, search, MTI, and image radar. Recommended foundation: E E 200, E E 340 and E E 496. Crosslisted with: E E 452.


EE 549 Smart Antennas
Smart antenna and adaptive array concepts and fundamentals, uniform and plannar arrays, optimum array processing. Adaptive beamforming algorithms and architectures: gradient-based algorithms, sample matrix inversion, least mean square, recursive least mean square, sidelobes cancellers, direction of arrival estimations, effects of mutual coupling and its mitigation. Recommended foundation: E E 325 and E E 340. Crosslisted with: E E 449.

EE 551 Control System Synthesis I
An advanced perspective of linear modern control system analysis and design, including the essential algebraic, structural, and numerical properties of linear dynamical systems.


EE 558 Hardware Security and Trust
This course introduces and investigates recent technology development for the design and evaluation of secure and trustworthy hardware and embedded systems. Topics include IoT security, cryptography, hardware security primitives, authentication and key generation, invasive and non-invasive attacks and countermeasures, IC piracy and intellectual property protection, hardware trojans, and secure boot. Recommended foundation: E E 212. Crosslisted with: E E 458.



EE 562 Computer Systems Architecture
The course covers uniprocessors, caches, memory systems, virtual memory, storage systems, with introduction to multiprocessor and distributed computer architectures; models of parallel computation; processing element and interconnection network structures, and nontraditional architectures. Recommended foundation is E E 212. Crosslisted with: E E 462.


EE 563 Computer Performance Analysis I
Issues involved and techniques used to analyze performance of a computer system. Topics covered include computer system workloads; statistical analysis techniques such as principal component analysis, confidence interval, and linear regression; design and analysis of experiments; queuing system analysis; computer system simulation; and random number generation. Recommended foundation: E E 200 and E E 462.


EE 564 Advanced Computer Architecture I
Multiprocessor and distributed computer architectures; models of parallel computation; processing element and interconnection network structures, and nontraditional architectures. Recommended foundation: E E 462. Crosslisted with: C S 573.


EE 565 Machine Learning I
A graduate-level introduction to machine learning algorithms, including supervised and unsupervised learning methods. Topics covered include clustering, linear regression models, linear discriminant functions, feed-forward neural networks, statistical pattern classification and regression, maximum likelihood, naive Bayes, non-parametric density estimation, mixture models, decision trees, and ensemble learning. Recommended foundation: E E 571 and MATH 480. Crosslisted with: E E 465.


EE 567 ARM SOC Design
The course aims to produce students who are capable of developing ARM-based SoCs from high level functional specifications to design, implementation and testing on real FPGA hardware using standard hardware description and software programming languages. Recommended foundation is E E 212 and E E 317. Crosslisted with: E E 467.


EE 569 Communications Network
Introduction to the design and performance analysis of communications networks with major emphasis on the Internet and different types of wireless networks. Covers network architectures, protocols, standards and technologies; design and implementation of networks; networks applications for data, audio and video; performance analysis. Recommended foundation: E E 100, E E 112 and (E E 200 or MATH 371). Crosslisted with: E E 469.


EE 571 Random Signal Analysis
Application of probability and random variables to problems in communication systems, analysis of random signal and noise in linear and nonlinear systems.


EE 572 Modern Coding Theory
Error control techniques for digital transmission and storage systems. Introduction to basic coding bounds, linear and cyclic block codes, Reed-Solomon codes, convolutional codes, maximum likelihood decoding, maximum a posteriori probability decoding, factor graphs, low density parity check codes, turbo codes, iterative decoding. Applications to data networks, space and satellite transmission, and data modems. Recommended foundation: E E 200 and E E 469.


EE 575 Machine Learning II
An advanced treatment of machine learning algorithms, including supervised, unsupervised, and reinforcement learning methods. Topics covered include kernel methods, maximum margin classification, support vector machines, generative topographic maps, diffusion maps, convolutional neural networks, recurrent neural networks, Hopfield networks, Boltzmann machines, deep belief networks, Markov chains, and hidden Markov models.
Prerequisite(s): E E 565.


EE 577 Fourier Methods in Electro-Optics
Linear systems theory, convolution and Fourier transformation are applied to one-dimensional and two dimensional signals encountered in electro-optical systems. Applications in diffraction, coherent and incoherent imaging, and optical signal processing. Recommended foundation: E E 320 and E E 528. Crosslisted with: PHYS 577.


EE 578 Optical System Design
Optical design software is used to study optical systems involving lenses, mirrors, windows and relay optics. Systems considered include camera lenses, microscopes and telecsopes. Recommended foundation: E E/PHYS 473, E E/PHYS 528 and E E/PHYS 577. Crosslisted with: PHYS 578.


EE 581 Digital Communication Systems I
Techniques for transmitting digital data over commercial networks. Topics include baseband and bandpass data transmission and synchronization techniques. Recommended foundation: E E 200, E E 325, and E E 496. Crosslisted with: E E 497.



EE 583 Wireless Communication
Cellular networks, wireless channels and channel models, modulation and demodulation, MIMO, diversity and multiplexing, OFDM, wireless standards including LTE and WiMAX. Recommended foundation: E E 571 and E E 325.



EE 584 Mathematical Methods for Communications and Signal Processing
Applications of mathematical techniques from estimation theory, optimization principles and numerical analysis to the problems in communications and signal processing. Recommended foundation: MATH 480.
Prerequisite(s): E E 571.



EE 585 Telemetering Systems
Covers the integration of components into a command and telemetry system. Topics include analog and digital modulation formats, synchronization, link effects, and applicable standards. Recommended foundation: E E 395, E E 496, and E E 497.


EE 586 Information Theory
This class is a study of Shannon's measure of information and discusses mutual information, entropy, and channel capacity, the noiseless source coding theorem, the noisy channel coding theorem, channel coding and random coding bounds, rate-distortion theory, and data compression. Restricted to: Main campus only. Crosslisted with: MATH 509
Prerequisite(s): E E 571 or MATH 515.


EE 588 Advanced Image Processing
Advanced topics in image processing including segmentation, feature extraction, object recognition, image understanding, big data, and applications. Crosslisted with: E E 444.
Prerequisite(s): E E 446 or E E 596.


EE 590 Selected Topics
May be repeated for a maximum of 18 credits.


EE 593 Mobile Application Development
Introduction to mobile application development. Students will develop applications for iOS devices including iPhone and iPad. Topics include object-oriented programming using Swift, model-view-controller (MVC) pattern, view controllers including tables and navigation, graphical user interface (GUI) design, data persistence, GPS and mapping, camera, and cloud and web services. Recommended foundation: C S 451 or C S 452. Crosslisted with: E E 443.


EE 596 Digital Image Processing
Two-dimensional transform theory, color images, image enhancement, restoration, registration, segmentation, compression and understanding. Recommended foundation: E E 395 and E E 571. Crosslisted with: E E 446.


EE 597 Neural Signal Processing
Cross-disciplinary course focused on the acquisition and processing of neural signals. Students in this class will be learn about basic brain structure, different brain signal acquisition techniques (fMRI, EEG, MEG, etc.), neural modeling, and EEG signal processing. To perform EEG signal processing, students will learn and use Matlab along with an EEG analysis package. Crosslisted with: E E 447.


EE 598 Master's Technical Report
Individual investigation, either analytical or experimental, culminating in a technical report. Graded PR/S/U. May be repeated up to 18 credits. Thesis/Dissertation Grading.


EE 599 Master's Thesis
Thesis. May be repeated up to 88 credits. Thesis/Dissertation Grading.


EE 600 Doctoral Research
Research.


EE 615 Computational Electromagnetics
The numerical solution of electromagnetics problems. Topics include differential equation techniques, integral equation methods, hybrid techniques, algorithm development and implementation, and error analysis. Particular algorithms, including FEM, finite differences, direct solvers, and iterative solvers, are studied.


EE 675 Machine Learning III
A research-oriented treatment of machine learning algorithms, including supervised, unsupervised, and reinforcement learning methods. Topics covered include Markov decision processes, deep reinforcement learning, neural logic networks, genetic algorithms, genetic programs, generative adversarial networks, and adaptive resonance theory models.
Prerequisite(s): E E 575.


EE 690 Selected Topics
May be repeated for a maximum of 9 credits.


EE 700 Doctoral Dissertation
Dissertation. May be repeated up to 88 credits. Thesis/Dissertation Grading.