Electrical Engineering Graduate Courses

Transcription

1 Electrical Engineering Graduate Courses ENEE 601 Signal and Linear Systems Theory [3] Fundamentals of signals and systems, mathematical theory of continuous and discrete systems, linear time invariant systems, linear time varying systems, state space model and approaches, stability, controllability and observability, minimal realizations. Co-requisite: ENEE 620. ENEE 608 Graduate Seminar [0] This course exposes the graduate student in EE to the current research in areas of interest to the department's faculty and students. The speakers are usually researchers outside, as well as inside, the department and university. On occasion, speakers may be faculty members or advanced students. There are no credits for this course, which meets once a week, but all graduate students are required to attend (one semester for master's students and two semesters for doctoral students). ENEE 610 Digital Signal Processing [3] This is a first-year graduate course for communication and signal processing majors in electrical engineering (EE) that covers the fundamentals of digital signal processing (DSP). The goal of this course is to provide the first-year EE graduate student with the foundations and tools to understand, design and implement DSP systems, in both hardware and software. MATLAB and SystemView will be the primary vehicles to provide the student with handson DSP design and simulation experience. The student also will acquire an understanding of DSP hardware basics and architecture. Topics covered include: (1) A/D-D/A conversion and quantization, number representations and finite wordlength effects; (2) FIR, IIR and lattice filter structures, block diagram and equivalent structures; (3) multirate DSP and filterbanks; (4) digital filter design methods and verification; (5) DSP hardware architecture; and (6) DSP simulation/ laboratory experiences. Prerequisite: ENEE 601, ENEE 620 or their equivalent or consent of instructor. ENEE 611 Adaptive Signal Processing [3] Fundamentals of adaptive filters and associated algorithms: mean-square error and least-squares approaches; steepest-descent algorithm; the least-mean-square adaptive filters, recursive least-squares adaptive filters, frequency domain and sub-band adaptive filters and unsupervised adaptive filters; analysis of these adaptive filters and discussion of selected applications. Prerequisites: ENEE 601 or ENEE 610 and ENEE 620 or consent of instructor. ENEE 612 Digital Image Processing [3] Principles of two-dimensional processing of image data: fundamentals of 2D signal processing, image transforms, image enhancement, image filtering and restoration, color image processing, image coding and wavelet quantization, image thresholding and segmentation, image interpretation and recognition, applications of image processing. Corequisite: ENEE 620, Prerequisite: MATLAB or consent of instructor. ENEE 620 Probability and Random Processes [3] Fundamentals of probability theory and random processes for electrical engineering applications and research: set and measure theory and probability spaces; discrete and continuous random variables and random vectors; probability density and distribution functions and probability measures; expectation, moments and characteristic functions; conditional expectation and conditional random variables; limit theorems and convergence concepts;

2 random processes (stationary/non-stationary, ergodic, point processes, Gaussian, Markov and second order); applications to communications and signal processing. Prerequisite: Undergraduate probability course work or consent of instructor. ENEE 621 Detection and Estimation Theory I [3] Fundamentals of detection and estimation theory for statistical signal processing applications; theory of hypothesis testing (binary, multiple and composite hypotheses and Bayesian, Neyman Pearson and minimax approaches); theory of signal detection (discrete and continuous time signals; deterministic and random signals; white Gaussian noise, general independent noise and special classes of dependent noise, e.g. colored Gaussian noise, signal design and representations); theory of signal parameter estimation; minimum variance unbiased (MVU) estimation; Cramer-Rao lower bound; general MVU estimation, linear models; maximum likelihood estimation, least squares; general Bayesian estimators (minimum mean-square error and maximum a posterior estimators); linear Bayesian estimators (Wiener filters) and Kalman filters. Prerequisite: ENEE 620 or consent of instructor. ENEE 622 Information Theory [3] Shannon's information measures: entropy, differential entropy, information divergence, mutual information and their basic properties. Entropy rates, asymptotic equipartition property, weak and strong typicality, joint typicality, Shannon's source coding theorem and its converse, prefix-free and uniquely decodable source codes, Huffman and Shannon codes, universal source coding, source-coding with a fidelity criterion, the rate-distortion function and its achievability, channel capacity and its computation, Shannon's channel coding theorem, strong coding theorem, error exponents, Fano's inequality and the converse to the coding theorem, feedback capacity, joint source channel coding, discrete-time additive Gaussian channels, the covering lemma, continuous-time additive Gaussian channels, parallel additive Gaussian channels and waterfilling. Additional topics: narrow-band time-varying channels, fading channels, side information, wideband channels, network coding, information theory in relation to statistics and geometry. Prerequisite: Strong grasp of basic probability theory. ENEE 623 Communication Theory I [3] A review of the Shannon capacity of the discrete-time additive Gaussian channel. Continuous-time additive Gaussian channels. Elementary signal design principles, baseband and passband pulse amplitude modulation, matched filtering, geometric representation of signals and optimum receivers. Orthogonal signaling and performance analysis, Shannon capacity, reliability function and cut-off rate. RS and BCH codes. Hard- and soft-decision decoding. Capacity approaching codes. Signaling in the band-limited region, Shannon capacity, pulse shaping, lattice codes, trellis codes, multi-level coding and constellation shaping. Equalization and precoding for linear Gaussian channels, waterfilling, multi-carrier signaling. Additional topics: signaling in fading media, multi-sensor and multi-user communications, synchronization. Prerequisites: ENEE 601, ENEE 621 and ENEE 622. ENEE 624 Error-Correcting Codes [3] Focusing on the fundamentals of art theory, criticism, analysis and evaluation, this course will examine contemporary art, theory and the historical and philosophical issues that shape and define art and culture. Note: Required course for the M.F.A. degree. ENEE 625 Data Compression [3] Principles and techniques of data compression: review of source coding theory; lossless data compression techniques, such as Huffman coding, bit-plane coding, predictive coding, arithmetic coding and LZW coding; and lossy data compression techniques, such as transform coding, wavelet transform coding, scalar quantitation, vector quantitation, predictive coding and sub-band coding. Prerequisites: ENEE 620 and ENEE 622 or consent of instructor. ENEE 630 Solid-State Electronics [3] Fundamentals of solid-state physics for the micro-electronics field: review of quantum mechanics and statistical

3 mechanics, crystal lattices, reciprocal lattices, dynamics of lattices, classical concepts of electron transport, band theory of electrons, semi-conductors and excess carriers in semi-conductors. Prerequisite: Consent of instructor. ENEE 631 Semiconductor Devices [3] Principles of semi-conductor device operation: review of semi-conductor physics, p-n junction diodes, bipolar transistors, metal semi-conductor contacts, JFETs and MESFETs and MIS and MOSFET structures. Prerequisite: ENEE 630 or consent of instructor. ENEE 632 Integrated Circuits [3] Fundamentals of bipolar and MOS analog and digital integrated circuit techniques: basic IC structure and fabrication, passive components, bipolar transistors and diode, characteristics matching, temperature compensation, output stages, frequency analysis, OpAmps, voltage regulators, multiplers, PLLs, MOS digital and analog circuits, memories, A/D converters, CMOS logic circuits. Prerequisite: ENEE 630, ENEE 631 or consent of instructor. ENEE 634 Microwave Device and Circuit Design [3] Basic concept and knowledge of microwave devices and integrated circuits for wireless communications, transmission lines and lumped elements, impedance matching networks, hybrids, couplers, filters, multiplexers, oscillators, amplifiers, detectors and mixers, microwave tubes or frequency multiplers, MMIC and laboratory. Prerequisite: ENEE 681 or consent of instructor. ENEE 635 Introduction to Optical Communications [3] Introduction to basic principles of optical communications: optical fibers, transmitters, receivers, optical system design and performance, optical amplifiers and multi-channel communication systems. Prerequisite: ENEE 630 or consent of instructor. ENEE 636 Introduction to Wireless Communications [3] Introduction to wireless communication systems, the cellular concept, mobile radio propagation, large-scale path loss and small-scale fading, multi-path modulation techniques, equalization, diversity, compression, multi-access techniques, wireless networking and wireless systems and standards. Prerequisite: Consent of instructor. ENEE 660 Systems Engineering Principles [3] This is a first-semester, required graduate course for Systems Engineering (SE) majors that covers the introduction to systems engineering. The course will address: (1) systems engineering principles; (2) systems engineering methodologies; (3) integration of technical disciplines; and (4) systems engineering management. The goal of this course is to provide the beginning graduate student with the foundational framework to understand requirements and capabilities-based design and how the traditional systems engineering process may need to adjust to accommodate these philosophies. The content of the course will result from the decomposition of system life cycle phases to illustrate the many engineering specialties and disciplines that are required to systematically engineer, deploy and sustain complex systems for missions to be performed in aerospace and electronics domains. The intent is to achieve a balance between understanding the system engineering process and its execution under differing design or acquisition philosophies. Prerequisite: B.S. degree in EE or related field. ENEE 661 System Architecture and Design [3] This is a required graduate course for the systems engineering (SE) track within the MSEE program. The course content includes both theoretical and practical considerations for developing of a system architecture and hardware and software system design within the overall systems engineering process. Major topics include development of an operational concept, functional decomposition, top-down vs. bottom-up techniques, requirements allocation and partitioning, interface definition, inclusion of integrity, reliability and maintainability within the design concept, validation and verification. The use of technical performance budgeting, quality function deployment techniques and

4 statistical and linear models in the design process will be discussed. Detailed examples of these techniques will be used to illustrate the various techniques. Prerequisite: B.S. degree in EE or related field. ENEE 660 (SE Principles) may be taken concurrently. ENEE 662 Modeling, Simulation and Analysis [3] This is a required course for the Systems Engineering (SE) track in the MSEE program. It is intended for those who wish to understand the art of building and using models and simulations for analysis. It covers the major types of models and simulations, their key features and the process of developing those simulations. Topics addressed include simulation architectures; cost and risk analysis; experimental design; simulation control and interfaces; languages and hardware platforms; requirements and architecture definition; simulation design and implementation; verification, validation and accreditation; estimating, planning and controlling simulation efforts; and the current state-of-the-art for simulation. Prerequisites: BS degree in EE or related field and a working knowledge of C/C++ or similar programming language. In addition, students are required to pass a Mathematics and MATLAB fundamentals test OR pass ENEE 669: Mathematics and MATLAB Fundamentals for Engineers. ENEE 663 System Implementation, Integration and Test [3] This is a second-semester, required graduate course for the Systems Engineering (SE) track within the MSEE program, which covers the conversion of a design into product elements, integration of these elements into a system and verification that the resulting system performs properly in its operational environment. The course will address: (1) the systems engineer's role in the product development organization; (2) processes used to manage product teams, technical budgets, baselines and schedules during product development; (3) integration methodologies and techniques for avoiding or resolving interface issues; and (4) types and methods of product testing. The goal of this course is to acquaint the EE graduate student with an understanding of the processes by which complex aerospace, information or other industry systems are built and tested by integrating the efforts of a large product team encompassing many engineering specialties, and the methods used for technical management of this team and the resulting product. Specific processes depend on the development environment and the product customer. This course emphasizes aerospace and information systems. Prerequisites: ENEE 660 and ENEE 661, or consent of instructor. ENEE 671 Service Oriented Architecture [3] This course examines the design consequences in following SOA architectural principles including: Encapsulation, Loose Coupling (Independence), Service Contract (for Communication), Service Abstraction (hiding logic), Reusability, Composability (coordination of composite services), Autonomy (control over encapsulated logic), Statelessness (retention of data from an activity) and Discoverability (finding and accessing services based upon intuitive identification). The course emphasizes the practical implementation of useful enterprise-wide systems using SOA. Working in teams, students will architect, design and implement a system project via simulation of performance and behavior. As result, students will gain fundamental knowledge and hands-on experience to permit them to function as individual contributors and integration leads in the context of an industrial environment. ENEE 680 Electromagnetic Theory I [3] Fundamentals of dynamics in electromagnetic theory: theoretical analysis of Maxwell's equations, electrodynamics, plane waves, waveguides, dispersion, radiating systems and diffraction. Prerequisite: Consent of instructor. ENEE 683 Lasers [3] Introduction to basic theory of lasers: introduction to quantum mechanics and time-dependent perturbation theory, interaction of radiation and matter, stimulated and spontaneous emissions, rate equations, laser amplification and oscillation, noise in lasers and laser amplifiers andsemi-conductor lasers. Prerequisite: ENEE 680 or consent of instructor. ENEE 684 Introduction to Photonics [3] This course covers the fundamentals of photonics and their applications. Subjects include crystal and polarization

5 optics, Jones calculus and Stokes parameters, polarization mode dispersion, fiber-optics, planar waveguide optics, electro-optics, acousto-optics, second- and third-order non-linear susceptibilities, second harmonic generation, sumfrequency generation, parametric down-conversion and oscillation, self-focusing, self- and cross-phase modulation, optical solutions, four-wave mixing, Raman scattering, Brillouin scattering, phase conjugation, photo-refractive optics, photo detectors and noise characteristics. Prerequisite: ENEE 680. ENEE 685/CMPE 485 Introduction to Communication Networks [3] The fundamentals of communication and computer networking, seven-layer OSI model, review of queuing models, transmissions, WDM, circuit and packet switching, data link and medium access technologies, X.25, frame relays, ISDN, xdsl, cable modem, SONET, the network layer, ATM, TCP/IP, routing techniques, the transport and application layers and quality of services (QoS). Prerequisite: Consent of instructor. ENEE 691 Topics in Electrical Engineering [3] ENEE 698 Research Project in Electrical Engineering (Systems Engineering Project) [1-3] Individual project on a topic in electrical engineering. The project will result in a scholarly paper, which must be approved by the student's advisor and read by another faculty member. Required of non-thesis option M.S. students. Note: May be taken for repeated credit up to a maximum of three credits. Prerequisite: Completion of core courses or consent of instructor. ENEE 699 Independent Study [1-3] Independent study of topics in electrical engineering. Prerequisite: Consent of instructor. ENEE 710 Digital Speech Processing [3] Fundamentals and techniques for the digital processing of speech: digital signal processing concepts review, speech production models, characteristics of the speech signal, time domain speech analysis, linear predictive coding (LPC), homomorphic speech processing, speech enhancement, speech recognition, speech coding and speech synthesis. Prerequisites: ENEE 610 and ENEE 611 or consent of instructor. ENEE 711 Neural Networks in Signal Processing [3] Fundamentals and characteristics of artificial neural network paradigms and their properties in association, learning, generalization and self-organization; introduction and survey of various neural network models and paradigms, multi-layer perceptron and the radial basis function networks; sum of squares and information-theoretic cost functions; different learning procedures (gradient optimization, conjugate gradients, Newton, etc.); learning and generalization properties; applications in communications and biomedical signal processing; and comparisons with linear adaptive signal processing theory and techniques. Prerequisite: ENEE 620 or consent of instructor. ENEE 712 Pattern Recognition [3] Principles of statistical pattern recognition; hypothesis testing and decision theory; parametric estimation (Bayesian estimation, maximum-likelihood estimation, Gaussian mixture analysis); non-parametric estimation (nearestneighbor rule and Pazen's window method); density approximation; linear discriminant functions; feature extraction and selection; feature optimization; neural networks (single-layer perceptrons, multi-layer neural networks); and applications in pattern classification. Prerequisites: ENEE 612, ENEE 620 and ENEE 621 or consent of instructor. ENEE 718 Advanced Topics in Signal Processing [3] ENEE 718 comprises advanced topic courses in signal processing that reflect the research interests of the faculty and their doctoral students. A specific offering under this title is designated by a letter appended to this course number and is generally not offered every year. Prerequisite: Depends on offering; consent of instructor.

6 ENEE 721 Statistical Signal Processing [3] Statistical inference. Point and interval estimation. State-space estimation. Elements of large- and small-sample theory. Array processing. Multi-channel signal processing. Reduced rank methods. Optimal and suboptimal multiuser detection. Low-complexity maximum likelihood detection. Iterative detection and its theoretical foundations. The relationship between statistical inference, statistical mechanics and information theory. Prerequisites: ENEE 620 and ENEE 621 or consent of instructor. ENEE 723 Multi-user Communication [3] This is an advanced course in wireless communication theory that focuses on several aspects of multi-user communication including current progress in multi-user Shannon theory, signaling schemes for wireless multiaccess, broadcast and interference channels, receivers for fading multi-user wireless channels, interference and power management, multi-antenna signaling, ultra-wideband signaling and the capacity and control of very large wireless networks. Prerequisites: ENEE 622 and ENEE 623 or consent of instructor. ENEE 728 Advanced Topics in Communications [3] ENEE 728 comprises advanced topic courses in communications that reflect the research interests of the faculty and their doctoral students. A specific offering under this title is designated by a letter appended to this course number and is generally not offered every year. Prerequisite: Depends on offering; consent of instructor. ENEE 737 Semi-conductor Device Processing Techniques [3] Introduction to basic semi-conductor device processing techniques: etching, photo-lithography, metalization and device characterization. Laboratory exercises will complement the lectures and demonstrate the principles. Prerequisites: ENEE 630 and ENEE 631 or consent of instructor. ENEE 738 Characteristics of Semi-conductor Opto-electronics [3] Introduction to current semi-conductor opto-electronic devices and survey of new research results: review of semiconductor physics and device characteristics; optical receiver concepts, such as photo-conductors, metal semiconductor concepts, MSM, pin, receiver design and APD; waveguide concepts, such as waveguide devices, waveguide modes, waveguide couplers, EO effects and modulation, periodic waveguides, polarization devices, waveguide filters, BPM and LED amplifier; and laser concepts, such as edge/surface emitting, optical gain, traveling wave amplifiers, FP, DFB, DBR, QW lasers, active filters, small-signal modulation, mode-locking, line width and noise. Prerequisites: ENEE 630, ENEE 631, ENE 680 and ENEE 683 or consent of instructor. ENEE 785 Advanced Topics in Optical Networks [3] This is an inter-disciplinary course to address the issues of importance in constructing high-speed optical networks. It covers the current networks for both telecoms and datacoms. Network layers, circuit switching and packetswitching principle and technologies are described. Depending on the instructor, technologies related to the physical layer of the system, protocols and traffic and network control will be covered in more detail. Projects are required for all students. Prerequisite: Depends on offering; consent of instructor. ENEE 788 Advanced Topics in Electrophysics and Photonics [3] ENEE 788 comprises advanced topic courses in photonics that reflect the research interests of the faculty and their doctoral students. A specific offering under this title, designated by a letter appended to this course number, is generally not offered every year. Prerequisite: Depends on offering; consent of instructor. ENEE 799 Master's Thesis Research [1-6] This course is for MSEE students engaged in master's thesis research; may be taken for repeated credits, but a

7 maximum of six credit hours can be applied toward master's thesis-option requirements. Must be taken over at least two semesters. Prerequisite: Open only to MSEE thesis-option students. ENEE 898 Pre-Candidacy Doctoral Research [1-6] Research on doctoral dissertation conducted under the direction of a faculty advisor before candidacy. ENEE 899 Doctoral Dissertation Research [6] Doctoral students must take this course over at least two semesters. Only a maximum of 12 credit hours can be applied toward the doctoral. requirements, and only six credit hours can be taken before admission to Ph.D. candidacy. Prerequisite: Open only to EE students who have passed the Ph.D. qualifying exam.