Electrical Engineering (EENG)
Department of Computer Science and Electrical Engineering
CHARLES NICHOLAS, Chair
GARY M. CARTER, Graduate Program Director
Professors
ADALI, TULAY, Ph.D., North Carolina State University; Statistical signal processing, machine learning for signal processing, adaptive signal processing and its applications in communications and biomedical data analysis (functional MRI, MRI, PET, CR, ECG and EEG)
CARTER, GARY M. Ph.D., Massachusetts Institute of Technology; Optical communications, non-linear optics, lasers, bio-photonics
CHANG, CHEIN-I, Ph.D., University of Maryland, College Park; Hyperspectral imaging, chemical/biological defense, automatic target recognition (ATR), computer-aided diagnosis for medical imaging, visual information systems and retrieval
CHEN, YUNG JUI (RAY), Ph.D., University of Pennsylvania; Optical networks, integrated optics and opto-electronic integrated circuits, device physics, ultra-fast optics and non-linear optics
CHOA, FOW-SEN, Ph.D., State University of New York, Buffalo; Opto-electronic devices, optical networks, optical materials
JOHNSON, ANTHONY, Ph.D., City College of the City University of New York; Director of the Center for Advanced Studies in Photonics Research (CASPR); Ultra-fast optics, non-linear optics and ultra-fast photophysics of nano-structured materials
MENYUK, CURTIS R., Ph.D., University of California, Los Angeles; Optical communications, non-linear optics, theoretical electromagnetics
MORRIS, JOEL M., Ph.D., The Johns Hopkins University; Communication theory, error correction codes, adaptive importance sampling for very low error rates, joint time-frequency/time-scale analysis
PINKSTON, JOHN, Ph.D., Massachusetts Institute of Technology; Coding theory, information security, antennas
YAN, LI, Ph.D., University of Maryland, College Park; Ultra-fast optics, non-linear optics, lasers, optical communications
Degrees Offered
M.S. (thesis and non-thesis), Ph.D., Graduate Certificate in Systems Engineering
Program Descriptions
The Department of Computer Science and Electrical Engineering offers a graduate program leading to the Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) degrees in Electrical Engineering (EE). The diversity of course offerings and research interests within the department and interactions with the medical and dental schools at the University of Maryland, Baltimore; the mathematics and physics departments at UMBC; and the electrical engineering department at University of Maryland, College Park, encompass a broad spectrum of inter-disciplinary or strictly electrical engineering instruction and research topics.
Areas of specialization in EE include:
- Communications (random processes, detection and estimation theory, information theory, source and channel coding, communication theory, wireline and wireless communication, optical fiber communications, data compression and applications of adaptive signal processing in communication)
- Micro-electronics (solid-state electronics, semiconductor devices and processing technology, semi-conductor opto-electronics, compound semi-conductor electronics and integrated circuits)
- Photonics (electromagnetic theory, quantum electronics, lasers, photonics, non-linear optics, fiber-optic communications and ultra-fast optics)
- Signal Processing (signal and linear system theory, digital signal processing, adaptive signal processing, speech processing, neural networks, pattern recognition, spectral and time-frequency analysis and biomedical signal processing)
- Image Processing (automatic target recognition, pattern recognition, neural networks, image coding and compression, multi-spectral/hyper-spectral imaging, medical imaging, visual information system and retrieval)
- Systems Engineering (life cycles of complex systems; system architecture and design; system modeling, simulation and analysis; system implementation, integration and test; and systems of systems). The systems engineering track is a non-thesis Master of Science in Electrical Engineering program.
Post-Baccalaureate Certificate in Systems Engineering
The graduate certificate program in systems engineering (SE) is a non-degree program requiring 15 credit hours, including the Systems Engineering Project course (ENEE 698). In the project course, the student performs an industry-based SE project and writes a related technical report/scholarly paper, which must be approved by the department. Normally, two faculty members must approve the ENEE 698 scholarly paper, but in this case, to encourage local industry and government partnership, the scholarly paper can be approved by the student’s advisor and an industry/government mentor approved by the department.
All systems engineering credits in the graduate certificate program are applicable toward a Master of Science in Electrical Engineering (MSEE) with a systems engineering track if the student is admitted to the MSEE program.
Students must take the following courses:
Four three-credit SE courses, plus a systems engineering project:
ENEE 660: System Engineering Principles
ENEE 661: System Architecture and Design
ENEE 662: System Modeling, Simulation and Analysis
ENEE 663: System Implementation, Integration and Test
ENEE 698: Systems Engineering Project
(Elective) ENEE 664: Systems of Systems
Degree Requirements
Master of Science (M.S.) Degree
Within five years of admission, the student must earn a minimum of 30 credit hours for the thesis option, 33 credit hours for the non-thesis option. Students must satisfy the GPA and course requirements for their field of specialty and attend the department’s Graduate Seminar (ENEE 608). Each student must complete either a thesis or a scholarly paper. The thesis option in the student’s field requires a minimum of eight graduate-level courses (24 credit hours) and six credit hours of thesis (ENEE 799).
The thesis must be defended with an oral exam and accepted with the approval of the student’s master’s thesis committee. A bound copy of the thesis must be submitted both to the department and the Graduate School. (The student’s thesis advisor also may require a bound copy of the thesis). The non-thesis option in the student’s field requires a minimum of 10 graduate-level courses (30 credit hours) and three credit hours of ENEE 698 research project work resulting in a scholarly paper that must be approved by the advisor and read by another faculty member. A copy of the scholarly paper must be submitted to the department.
Breadth Courses
Students must take either three or four breadth courses in their chosen field with a grade of “B” or better in each course (each field may have additional GPA requirements).
Thesis-Option (30 credits) Requirements for Micro-electronics and Photonics
Students must take the following breadth courses:
ENEE 630: Solid-State Electronics
ENEE 631: Semi-conductor Devices
ENEE 680: Electromagnetic Theory I
ENEE 683: Lasers
ENEE 799: Thesis (six credits)
Students also are required to take two of the following elective courses (six credits) from technical electives in micro-electronics and photonics:
ENEE 632: Integrated Circuits
ENEE 634: Microwave Devices and Circuits
ENEE 635: Intro to Optical Communications
ENEE 636: Intro to Wireless Communications
ENEE 684: Intro to Photonics
ENEE 685: Intro to Communication Networks
ENEE 735: Photonics Integrated Circuits
ENEE 736: Intro to Optical Communication Systems
ENEE 737: Semi-conductor Device Processing Techniques
ENEE 738: Characteristics of Semi-conductor Opto-electronics
ENEE 785: Topics in Optical Networks
ENEE 788: Topics in Photonics
And students are required to take two 600-/700-level, advisor-approved courses.
Non-Thesis-Option (33 credits) Requirements for Micro-Electronics and Photonics
Students must take the following breadth courses:
ENEE 630: Solid-State Electronics
ENEE 631: Semi-conductor Devices
ENEE 680: Electromagnetic Theory I
ENEE 683: Lasers
ENEE 698: Graduate Project (with scholarly paper)(three credits)
Students also are required to take four of the following elective courses (12 credits) from the micro-electronics and photonics area:
ENEE 632: Integrated Circuits
ENEE 634: Microwave Devices and Circuits
ENEE 635: Intro to Optical Communications
ENEE 636: Intro to Wireless Communications
ENEE 684: Intro to Photonics
ENEE 685: Intro to Communication Networks
ENEE 735: Photonics Integrated Circuits
ENEE 736: Intro to Optical Communication Systems
ENEE 737: Semi-conductor Device Processing Techniques
ENEE 738: Characteristics of Semi-conductor Opto-electronics
ENEE 785: Topics in Optical Networks
ENEE 788: Topics in Photonics
And students are required to take two additional 600-/700-level, advisor-approved courses (can include a maximum of three credits from ENEE 699 in addition to the required ENEE 698, which results in a scholarly paper).
Thesis-Option (30 credits) Requirements for Communications and Signal Processing
Students must take the following breadth courses:
ENEE 601: Signal and Linear Systems Theory
ENEE 620: Probability and Random Processes
ENEE 621: Detection and Estimation Theory I
ENEE 799: Master’s Thesis Research (six credits)
Students must also take three of the following elective courses (nine credits)
ENEE 61X, ENEE 62X, ENEE 71X, ENEE 72X, ENEE 63X, ENEE 68X, ENEE 73X or ENEE 78X, where X is any number in that sequence. Students must take two additional 600-/700-level, advisor-approved courses.
Non-Thesis-Option (33 credits) Requirements for Communications and Signal Processing
Students must take the following breadth courses:
ENEE 601: Signal and Linear Systems Theory
ENEE 610: Digital Signal Processing
ENEE 620: Probability and Random Processes
ENEE 621: Detection and Estimation Theory I
ENEE 698: Project in Electrical Engineering (with scholarly paper) (three credits)
Students are also required to take four of the following elective courses (12 credits)
ENEE 61X, ENEE 62X, ENEE 71X, ENEE 72X, ENEE 63X, ENEE 68X, ENEE 73X or ENEE 78X, where X is any number in that sequence.
Students are required to take two additional 600-/700-level, advisor-approved courses (can include a maximum of three credits from ENEE 699 in addition to the required ENEE 698, which results in a scholarly paper).
Requirements for Systems Engineering Track
The systems engineering track within the M.S. in Electrical Engineering is a non-thesis program. Students must earn 33 credit hours, including the Systems Engineering Project course (ENEE 698). In the project course, the student performs an industry-based SE project and writes a related technical report/scholarly paper that must be approved by the department. Normally, two faculty members must approve the ENEE 698 scholarly paper, but in this case, to encourage local industry and government partnership, the scholarly paper can be approved by the student’s advisor and an industry/government mentor approved by the department.
Students must take four three-credit courses from the following eight core EE courses:
Micro-electronics and Photonics Specialization:
ENEE 630: Solid State Electronics
ENEE 631: Semiconductor Devices
ENEE 680: Electromagnetic Theory
ENEE 683: Lasers
Communications and Signal Processing Specialization:
ENEE 601: Signal and Linear Systems
ENEE 610: Digital Signal Processing
ENEE 620: Probability and Random Processes
ENEE 621: Detection and Estimation
Four three-credit systems engineering courses:
ENEE 660: System Engineering Principles
ENEE 661: System Architecture and Design
ENEE 662: System Modeling, Simulationand Analysis
ENEE 663: System Implementation, Integration and Test
ENEE 664: Systems of Systems
Two three-credit graduate technical electives (advisor approved) from EE, SE (such as ENEE 664), Civil Engineering, Computer Engineering, Computer Science, Information Systems, Mathematics, Mechanical Engineering or Physics.
ENEE 698: Systems Engineering Project
A grade of “B” (3.0 GPA) or betterin all breadth courses and a minimum of 3.0 GPA overall are required. Unless approved by the graduate program director, each student is allowed to take a maximum of six credits of courses outside the department. These courses must be at the graduate level and must be approved by the student’s advisor and the graduate program director prior to registration.
Research Courses
Research courses provide the course credits for the student’s research activities, e.g., ENEE 699; Independent Study, ENEE 698: Graduate Project, and ENEE 799: Master’s Thesis.
Graduate Seminar
Each student must attend the department’s graduate seminar course (ENEE 608) for one semester.
M.S. Comprehensive Examinations
The comprehensive examination is not required for M.S. (EE) students. A Master’s (EE) student planning to pursue a doctoral degree may choose to take this exam before completing the master’s degree requirements.
M.S. Thesis Option
M.S. students choosing the thesis option must undertake Master’s Thesis (ENEE 799), which is supervised by a faculty member as the thesis advisor. Upon completion of the thesis research and document, the thesis must be defended in a public presentation. The required six credits of ENEE 799 must be taken over two or more semesters.
Scholarly Paper
M.S. students choosing the non-thesis option must undertake Graduate Project (ENEE 698), which is supervised by a faculty member as the graduate project and scholarly paper advisor. Upon completion of the graduate project and document, the scholarly paper must be approved by the advisor and a second faculty member.
Transfer Credits
No more than six credits may be transferred from another university or from UMBC as a non-degree student. Credit transfer must be approved by the graduate program director.
Doctor of Philosophy (Ph.D.) Degree
Each specialty area (communications and signal processing, micro-electronics and photonics) sets its course requirements for doctoral students in that specialty. The department’s minimum requirement is 11 courses, excluding graduate seminar participation, graduate research credits prior to Ph.D. candidacy and doctoral dissertation research credits (ENEE 899). Four of these 11 courses must be taken at UMBC (at least two of these courses have to be ENEE courses). The doctoral dissertation must be an original and substantive contribution to knowledge in the student’s major area and must demonstrate the student’s ability to carry out a program of research and report the results in accordance with standards observed in the recognized scientific journals related to that area. Students are expected to present their results formally at conferences and/or in technical journals related to their specialty area.
The Ph.D. student must:
- Pass the written comprehensive exam (comps) within four semesters of entrance to the program (five semesters for part-time students). The comps are based on the core courses for the student’s area of specialty to assess his or her mastery of fundamental knowledge and skills. Micro-electronics and photonics students must take the comps in ENEE 630, ENEE 631, ENEE 680 and ENEE 683. Communications and signal processing students must take the comps in ENEE 601, ENEE 620, ENEE 621 and ENEE 622. The comps will be offered twice a year between the semesters (typically in January and August). Each doctoral student must pass the EE comps within the first four semesters of admission to the Ph.D. program (first five semesters for part-time students). All students must pass the comps within two attempts, or they will be dismissed from the doctoral program. See the graduate program Web site for detailed policies for comprehensive exams.
- Develop and defend a doctoral dissertation proposal (preliminary exam) and be admitted to Ph.D. candidacy within four years of entrance to the program (five years for part-time students).
- Complete all Ph.D. requirements for their area of specialty within four years after admission to Ph.D. candidacy.
Graduate Seminar
Each student must attend the department’s Graduate Seminar course (ENEE 608) for two semesters, usually during his or her first year.
Course Requirements
Students must satisfy the minimum course requirements for their field of specialty as indicated below (typically 11 courses totaling 33 credit hours), excluding the department’s graduate seminar, graduate research credits prior to Ph.D. candidacy and doctoral dissertation research credits.
Ph.D. Requirements for Photonics and Micro-electronics
Students must take the following breadth courses:
ENEE 630: Solid-State Electronics
ENEE 631: Semi-conductor Devices
ENEE 680: Electro-magnetic Theory I
ENEE 683: Lasers
Students also are required to take four electives from the list below, at least two of them being 700-level:
ENEE 632: Integrated Circuits
ENEE 634: Microwave Devices and Circuits
ENEE 635: Intro to Optical Communications
ENEE 636: Intro to Wireless Communications
ENEE 684: Intro to Photonics
ENEE 685: Intro to Communication Networks
ENEE 735: Photonics Integrated Circuits
ENEE 736: Intro to Optical Communication Systems
ENEE 737: Semi-conductor Device Processing Techniques
ENEE 738: Characteristics of Semi-conductor Opto-electronics
ENEE 785: Topics in Optical Networks
ENEE 788: Topics in Photonics
And students are required to take any three additional advisor-approved graduate courses (can include a maximum of three credits from ENEE 698 or ENEE 698).
Comprehensive Exam Courses:
ENEE 630: Solid-State Electronics
ENEE 631: Semi-conductor Devices
ENEE 680: Electro-magnetic Theory I
ENEE 683: Lasers
Ph.D. Requirements for Communications and Signal Processing
Student must take the following breadth courses:
ENEE 601: Signal and Linear Systems Theory
ENEE 620: Probability and Random Processes
ENEE 621: Detection and Estimation Theory I
ENEE 622: Information Theory
Students also are required to take four elective courses (12 credits) from
ENEE 61X, ENEE 62X, ENEE 71X, ENEE 72X, ENEE 63X, ENEE 68X, ENEE 73X or ENEE 78X (where at least two are 700-level or higher and where X is any number in that sequence)
In addition, students are also required to take any three additional advisor-approved graduate courses (can include a maximum of three credits from ENEE 698 or ENEE 699), one of which must be a MATH/STAT course (600-level or higher).
Comprehensive Exam Courses
ENEE 601: Signal and Linear Systems Theory
ENEE 620: Probability and Random Processes
ENEE 621: Detection and Estimation Theory I
ENEE 622: Information Theory
For All Areas
A grade of “B” (3.0 GPA) or better is required in all courses and a minimum of 3.33 GPA overall (including the transfer courses).
Course Requirements
Students must satisfy the minimum course requirements for their area of specialty, excluding the department’s EE graduate seminar, graduate research credits prior to Ph.D. candidacy (ENEE 800 and ENEE 899) and doctoral dissertation research credits (ENEE 899). Students may take up to six dissertation research credits (ENEE 899) after passing the comprehensive examination and before being admitted to Ph.D. candidacy.
Preliminary Examination (Prelim)
Students must select a dissertation advisor and a dissertation preliminary examination committee, and they must pass a two-part preliminary examination. In the first part, students will present and defend their dissertation proposal to the preliminary committee.
In the second part, the committee examines the students orally on their proposal and research area(s) to assess their ability to complete the proposed research. Each full-time student must pass the preliminary exam within one-and-a-half years after passing the comps to remain in the Ph.D. program (part-time students will be given two-and-a-half years to pass the prelim).
Ph.D. Candidacy
After passing the preliminary exam and completing the course requirements, the graduate program committee recommends to the Graduate School that the student be admitted to Ph.D. candidacy.
Dissertation Research
Students will conduct and report on a significant original research project under the guidance of their dissertation advisor. This research must be completed and defended within four years of admission to candidacy. Students must be admitted to candidacy at least two full sequential semesters before the date on which the doctoral degree is to be conferred.
Residency Requirements
A minimum of three years of full-time graduate study or its equivalent is required. At least one year of full-time study must be completed at UMBC.
Program Admission Requirements
When seeking admission to the graduate program in electrical engineering, applicants must satisfy all entrance requirements of the Graduate School at UMBC. These include the submission of transcripts, letters of recommendation, statement of purpose, the results of the Graduate Record Examination (GRE Aptitude) and, for foreign students, scores for the TOEFL. Students transferring from another graduate program also must, include a letter from the graduate director of their program. All original application materials must be sent directly to the Graduate School, not the graduate program. Application deadlines are specified by the Graduate School. The application review process will begin by January 1 for admission in the fall semester and by October 1 for admission in the following spring semester. Early application is recommended.
Minimum requirements for admission to the graduate program in electrical engineering are a B.S. degree from an ABET-accredited undergraduate program in electrical engineering with a GPA of “B+” or higher. Individuals whose records indicate strong potential for successful pursuit of the master’s or doctoral degree objectives and who have similar undergraduate preparation with strong academic records in computer science, mathematics, physics or other areas of engineering or science are encouraged to apply (B.S. degrees in engineering technology are not considered equivalent to the B.S. degree in engineering or the B.A. degree in the sciences). Students whose degrees are not in electrical engineering generally will be required to take courses to make up deficiencies in their backgrounds. Graduate Record Exam (GRE) scores are required for admission and TOEFL scores are required for foreign students. Applicants are judged competitively by the department’s admissions committee, and those who appear suitably qualified to complete the requirements of the intended degree program successfully are selected for admission, subject to available resources. Applications are not processed until all documents and fees are received.
Facilities and Special Resources
Faculty and students in the electrical engineering program at UMBC have access to extensive computational resources. The research and instructional activities of the department are supported by a number of new modern laboratories. Laser-based laboratories support research in ultra-fast non-linear optics and optical spectroscopy, optical communications, diode laser physics, novel diode laser structures and optical fiber lasers. Device fabrication laboratories support research in optical and electronic properties of compound semi-conductors and organic polymers and in exploring and developing new materials, sub-micron device structures and processing technologies via CAIBE. Compound semi-conductor growth research is being pursued using MOCVD techniques. A new remote sensing signal and image processing laboratory supports research in multi-spectral and hyper-spectral imagery, pattern recognition, target tracking and detection, image coding and progressive image transmission, computer vision and medical imaging. The Statistical Signal Processing Laboratory (SSPL) supports research in theory and algorithms in adaptive and/or non-linear signal processing for communications (optical, wireless and wireline) and for biomedical image analysis. The laboratory has active collaborations with a number of institutions in the area, such as the Kennedy Krieger Center at Johns Hopkins and the Department of Radiology at the University of Maryland Medical School (UMMS), as well as a number of international research groups, such as the Intelligent Signal Processing group at Denmark Technical University. The research in SSPL is supported by NSF, NASA, NIH and grants from the industry and the Maryland Industrial Partnerships Program. The optical communications laboratory contains high-performance, fiber-optics communication equipment to perform experiments in digital transmission using multi-channels over long distances.
Financial Assistance
Financial aid is available on a competitive basis to a limited number of qualified graduate students in the form of graduate teaching assistantships (TAs), graduate research assistantships (RAs), work-study positions and hourly employment as graders. Graduate RAs are often available to students actively engaged in a master’s thesis or doctoral dissertation research and are awarded and renewed subject to availability of funds and satisfactory research progress. Students are encouraged to apply directly to nationally awarded fellowship programs.
COURSE LISTING
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 hands-on 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) multi-rate 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. Co-requisite: 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; 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]
Fundamentals of error-correction coding theory: linear block and trellis codes, decoder structures, random and burst error detection and correction techniques, encoding/decoding performance and bounds, concatenated codes and interleaving structures, turbo and LDPC codes and iterative decoding concepts. Prerequisites: ENEE 620 and ENEE 622 or ENEE 623, or consent of instructor.
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 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
Semi-conductor 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 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: B.S. degree in EE or related field and a working knowledge of C/C++ or a similar programming language, ENEE 660 and ENEE 661 or consent of instructor.
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]
Service Oriented Architecture is an architectural style for creating enterprise-wide IT systems to allow businesses to preserve and reuse existing IT components while evolving their business models. This course examines the consequences in following service-orientation principles including: Encapsulation, Loose Coupling (independence), Service Level Agreement (a contract for Communication), Service Abstraction (hiding logic), Reusability, Composability (coordination of composite services), Autonomy (control over encapsulated logic), Statelessness (retention of date from an activity) and Discoverability (finding and accessing services based upon intuitive identification). Prerequisities: ENEE 662 and ENEE 698
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 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, sum-frequency 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 698
Research Project in Electrical Engineering [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 698
Research Project in Electrical Engineering (Systems Engineering Project) [1-3]
This is an individual industry-based systems engineering project. The project will result in a technical report/scholarly paper, which must be approved by the student’s advisor and an industry/government mentor approved by the department.
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 (nearest-neighbor 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
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.
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 multi-user 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 multi-access, 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
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 semi-conductor physics and device characteristics; optical receiver concepts, such as photo-conductors, metal semi-conductor 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
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 packet-switching 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
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 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 800
Graduate Research [1-6]
This course is for doctoral students not yet admitted to doctoral candidacy and can be taken for repeat credit. Prerequisite: Open only to EE students who have passed the Ph.D. qualifying exam.
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.