Department of Electrical Engineering
and Applied Physics
516 Glennan Building (7221)
phone 368-4088; fax 368-2668
Robert Trew; e-mail: rjt2@po.cwru.edu
Electrical engineering is a broad, dynamic field offering a great diversity of career opportunities in areas such as microwave and radio frequency communications, microprocessor-based digital control systems, robotics, solid state microelectronics, signal processing, and intelligent systems. The Department of Electrical Engineering and Applied Physics offers Bachelor of Science in Engineering, Master of Science in Electrical Engineering, Master of Engineering, and Doctor of Philosophy degree programs which provide preparation for work in these areas. The department offers a minor in electrical engineering for bachelor's degree students in other engineering disciplines as well as a minor in electronics for bachelor's degree students enrolled in the College of Arts and Science.
Robert J. Trew, Ph.D. (University of Michigan)
George S. Dively Distinguished Professor of Engineering and Chair
Microwave solid state devices and circuits; Computer-aided design; Characterization techniques
Robert E. Collin, Ph.D. (Imperial College, University of London, England)
Professor
Electromagnetic theory; antennas; propagation; microwave components and systems.
Steven L. Garverick, Ph.D. (Massachusetts Institute of Technology)
Associate Professor
Microelectronics; analog and digital circuit design.
Dov Hazony, Ph.D. (University of California, Los Angeles)
Professor; Director, Hans Jaffe Ultrasonics Laboratory
Network synthesis; ultrasonics; communications
Michael Huff, Ph.D. (Massachusetts Institute of Technology)
Assistant Professor
Solid-state sensors, microelectromechanical systems, biomedical applications.
Mehran Mehregany, Ph.D. (Massachusetts Institute of Technology)
Microelectromechanical systems, microsensors and microactuators, microfabrication technology, silicon carbide semiconductor technology, and integrated circuits
Francis L. Merat, Ph.D. (Case Western Reserve University)
Associate Professor
Computer vision; industrial inspection; intelligent process planning and CAE systems; optical and micro-opto-mechanical devices
Wyatt S. Newman, Ph.D. (Massachusetts Institute of Technology)
Associate Professor
Mechatronics; high-speed robot design; force and vision-based machine control; artificial reflexes for autonomous machines; rapid prototyping; agile manufacturing
Stephen M. Phillips, Ph.D. (Stanford University) P.E. (Ohio)
Associate Professor
System identification and feedback control; nonlinear, adaptive, sampled-data and multi-rate control; Applications to manufacturing, aeronautical electromechanical and microelectromechanical systems.
Massood Tabib-Azar, Ph.D. (Rensselaer Polytechnic Institute)
Associate Professor
Electronic devices and their applications in mobile communication circuits. Novel instrumentation methods and characterization and modeling of electronic defects in materials and devices. Quantum computing.
David Smith, Ph.D. (Massachusetts Institute of Technology)
Professor
Optical communications, devices and systems; fiber-optic networks; lasers
The undergraduate program in electrical engineering, which leads to the Bachelor of Science in Engineering degree, provides a broad foundation in electrical engineering through combined classroom and laboratory work and prepares the student for entering the profession of electrical engineering as well as for further study at the graduate level. The program is built upon three sets of core courses which collectively provide the student with a strong background in mathematics and the physical sciences (Case Core), a breadth of background in engineering (Engineering Core), and a fundamental knowledge of all aspects of electrical engineering (Electrical Engineering Core).
The Electrical Engineering Core courses include analog and digital electronics, microprocessors, electromagnetic fields, semiconductor electronic devices and electronic properties of materials, communications and signal analysis, and control.
In consultation with a faculty advisor, the student completes the program by selecting elective courses or course sequences that provide in-depth training in one or more of a variety of specialties such as digital and microprocessor-based control, communications and electronics, microwaves and solid state electronics and integrated circuit design and fabrication. Students can emphasize other specialties by selecting elective courses from other departments.
The undergraduate degree cannot provide complete professional preparation by itself but rather provides a general education in the field of electrical engineering. Our graduates have a firm foundation in mathematics and science, a working knowledge of the technology and practice of electrical engineering from our department courses, and an understanding of the social, cultural, and political context of our society gained through a study of the social sciences and humanities. Our curriculum prepares our B.S. graduates for entry-level positions which require conceptual design capability using scientific principals and mathematical tools. The undergraduate program also prepares our graduates for additional specialization and education through graduate, professional and continuing education programs.
Many courses have integral or associated laboratories in which students gain "hands-on" experience with electrical engineering principles and equipment. Students have ready access to the laboratory facilities and are encouraged to work in the various laboratories during nonscheduled hours in addition to the regularly scheduled laboratory sessions. A required two-semester laboratory during the senior year provides students, working in small groups, the opportunity to carry out the engineering design, construction, and testing of a significant device or system, or to carry out an appropriate research project. Opportunities also exist for undergraduate student participation in many of the wide variety of research projects being conducted within the department.
We define engineering design as the creative process of identifying needs and then devising a product to meet those needs. Engineering design is taught in an evolutionary manner in our curriculum. Sophomores learn basic engineering science, q.v. digital and analog electronics, and computer principles in EEAP 245, EEAP 246 and EEAP 282. Engineering design is based upon instructor defined goals with clear solutions methods typically based upon material taught within that course.
Juniors learn more mathematically intensive engineering science such as electromagnetic fields, solid-state physics, control theory, and advanced circuit theory. Selected courses such as EEAP 344 and EEAP 382 emphasize engineering design. Design problems are still instructor defined but are much more open-ended than in the sophomore year and typically require the integration of material from several courses. Students often work in teams and design goals are less well-defined than in the sophomore year with multiple solution methods possible. The senior year attempts to bridge the gap between engineering design as studied in school and the actual practice of engineering. Students are required to take a year long engineering design course tackling significant problems suggested by department faculty and staff, faculty and staff from other departments, industry, and the students themselves. The projects typically cover a wide range of topics, e.g., a limb controller for an robotic cockroach to designing a low-cost timer relay for a local company.
Students, in collaboration with a project advisor and the course instructor are taught a methodical approach to engineering design projects. This methodology includes design overview, actual problem solving, and project planning. Students are required to prepare a project proposal which delineates project goals and responsibilities, presents a preliminary budget, and includes a schedule with milestones which allows for ordering and receiving project components. Communications skills are honed by oral project briefings and presentations, and scheduled reports.
Undergraduate students who maintain at least a 3.0 grade point average may, with the consent of the faculty advisor, enrich their studies by electing specified graduate-level courses in the senior year. The department also encourages students with at least a 3.5 grade point average to apply for admission to the five year bachelors/master's program in the junior year. This integrated program, which permits substitution of M.S. thesis work for the senior laboratory project, provides a high level of fundamental training and in-depth advanced training in the student's selected specialty. It also offers the opportunity to complete both the Bachelor of Science in Engineering and Master of Science degrees within five years. The department provides an opportunity for significant financial aid in the form of tuition remission and a stipend to these students in their fifth year.
Students enrolled in degree programs in other engineering departments can have a minor specialization by completing the following courses:
EEAP 245, Electronic Circuits I (3)
EEAP 246, Electrical Circuits II (5)
EEAP 282, Assembly Language Programming (4)
EEAP 309, Electromagnetic Fields I (3)
Approved Course Elective (3)
The department also offers a minor in electronics for students in the College of Arts and Science. This program requires the completion of 29 credit hours, of which 10 credit hours may be used to satisfy portions of the students' skills and distribution requirements. The following courses are required for the electronics minor:
MATH 125, Mathematics I (4)a
MATH 126, Mathematics II (4)a
PHYS 115, Introductory Physics I (3)b
PHYS 116, Introductory Physics II (3)b
CMPS 131, Elementary Computer Programming (3)
EEAP 240, Electronic Circuits (4)
ECMP 280, Digital Logic Design (3)
EEAP 282, Assembly Language programming (4)
EEAP 309, Electromagnetic Fields I (3)
The department offers graduate programs leading to the Master of Science and Doctor of Philosophy degrees. The programs are comprehensive and basic, emphasizing four major areas in which the faculty are actively engaged in research: (1) automation, sensing, intelligence and actuation; (2) solid state electronics; (3) electromagnetics, high frequency communications and devices; and (4) Circuits, Signal Processing, and Computer-Aided Design. Academic requirements for graduate degrees in engineering are as specified for the Case School of Engineering in this bulletin, however, some exceptions are noted below. All current rules and regulations for this department are detailed in a graduate student handbook, available from the department office, which supersedes any rules contained here. A number of teaching and research assistantships are available, on a competitive basis, for the full support of qualified students. In addition, a limited number of tuition assistantships are also available for partial support of graduate students.
Each Master of Science candidate must complete a minimum of 27 credit hours of course work, which may include a maximum of one approved non-core 300-level course, beyond the B.S. degree. These credits may be distributed in one of two ways. Under Plan A, the typical program, the student takes at least 18 credit hours of approved course work (six courses) and completes a minimum nine-credit-hour M.S. thesis. A second option, Plan B, which is subject to the advisor's approval, requires 21 or 24 credit hours of approved course work and completion of a six or three-credit hour project. All M.S. students are required to submit a program of study, for approval by the advisor, the department chairman, and the dean of the Case School of Engineering, no later than the beginning of the second semester (third semester for part-time students). (Occasionally students may be required to take additional courses for background expansion.) A minimum grade point average of 3.2 is required to complete the degree.
The Doctor of Philosophy degree program requires completion of 18 credit hours of course work (400 level or above) beyond that required for the M.S. degree, achievement of a passing grade on the Ph.D. qualifying examination, and completion of an 18-credit-hour comprehensive research dissertation. Students in the Ph.D. program must submit a program of study for approval by the advisor, the department chairman, and the dean of the Case School of Engineering, by the beginning of the second semester following admission to the program. A minimum grade point average of 3.5 is required to complete the degree. The courses must be chosen so that, along with those taken for the M.S. degree, the following distribution requirement is satisfied:
A minimum of 18 credit hours of courses directly related to the student's research specialization. (These are usually, but not necessarily, from the Department of Electrical Engineering and Applied Physics.)
A minimum of 12 credit hours of approved courses not directly related to the research specialization. These may include courses chosen from any of the engineering departments as well as the Department of Physics.
A minimum of six credit hours of approved graduate-level mathematics courses.
Admission to candidacy for the Ph.D. degree requires completion of the M.S. degree or its equivalent and achievement of passing grades on the departmental written comprehensive examination. The comprehensive examination covers material at an advanced undergraduate level.
The comprehensive exam should be taken before completing 12 credit hours of Ph.D. course work.
A second stage requires a research examination to be taken before completing 12 credit hours of Ph.D. thesis. Research examination is taken not later than the end of the semester of first Ph.D. dissertation registration, and it is often a thesis proposal which assesses preparation for research at the Ph.D. level.
The department expects Ph.D. students to be in residence for at least one academic year.
English competency, required of all Ph.D. candidates, is assessed by the written proposal for thesis research and the oral presentation for this exam. Students whose mastery of English is found lacking will be required to satisfy this requirement by further remedial English course work.
The faculty of the department actively pursue research in the areas described below. A research brochure is available on request. Students pursue their thesis research under the supervision of a faculty member who is a recognized authority in his field. Support for thesis research comes from a related research project or program under the direction of the faculty. For further information on research opportunities, the department chairman should be contacted.
Research activities include: design, modeling, fabrication, and testing of microsensors; microactuators; micro-opto mechanical devices; microelectromech-anical systems; silicon carbide materials, processing, and device research; electronic devices in mobile communication circuits; microfabrication and integrated circuit process development.
Research activities include: neural network applications; pattern recognition; artificial intelligence; process automation; intelligent machine tool control; in-process gauging and control; adaptive learning methods applicable to robotics; system identification and adaptive control; intelligent control; the application of artificial intelligence to robotic systems and manufacturing; compliant control of robotic systems; non-contact inspection of production quality; machine vision for robotic applications; agile manufacturing systems; machine vision and image processing; rapid prototyping of computer-generated, 3-D objects in engineering materials; computational intelligence, principles and applications; distributed computational intelligence in network client/server mode; computational intelligence, object-oriented databases and associative memories
Research activities include: electromagnetic propagation and scattering, multiple-wavelength optical communications systems, integrated optics, optical amplifiers, acousto-optic filters and switches for wavelength-division multiplexed systems; design, analysis and modeling of high-frequency semiconductor devices and circuits, high frequency acoustic circuits, generation and detection of extremely sharp pulses, in situ monitoring in aggressive environments
Circuits, Signal Processing, and Computer-Aided Design Research activities include: neural network signal and information processing; image processing, mixed-signal integrated circuit design, CMOS integrated circuit design, microwave circuit computer-aided design, physical device models, harmonic balance techniques.
Extensive facilities are available within the department for the support of both instructional and research programs.
Departmental instructional laboratories include the Electronic Circuits Laboratory, with 18 basic low frequency work stations and 12 advanced work stations for circuit analysis; the Lester J. Kern Computational Laboratory, with Hewlett-Packard UNIX workstations, in-circuit emulators and logic analyzers, and the Electromechanical Energy Conversion Laboratory, with four computer-controlled experimental stations. The facilities of some of the instructional laboratories are available, on a non-interference basis, to students conducting graduate research. In addition, students use and have free access to the School of Engineering's Smith Computer Laboratory, which houses a variety of Macintosh, Pentium and UNIX based desktop computers.
Research laboratories within the department include:
- Micro-Opto-Mechanical Devices Laboratory with lasers and optical instrumentation; and Microwave Circuits CAD Laboratory equipped with Hewlett-Packard workstations, supporting printers and other equipment; microwave CAD software including HP's Microwave Design System (MDS), Silvaco's Pisces and Atlas, and many other software packages.
- Micro-electronic Device Modeling and Characterization Lab equipped with dc measurement capabilities for evaluating semiconductor device performance. Device modeling is done on Sun SPARC and HP workstations.
- Integrated Circuit Design/Test facility equipped with PC design workstations, integrated circuit test station, and a variety of integrated circuit test equipment.
- Integrated Optics Research Laboratory containing design facilities for integrated-optic devices; laser sources for multi-wavelength communication, RF and optical spectrum analyzers, optical amplifiers, integrated-optic device evaluation facilities, light-duty lithium niobate device processing lab.
In addition, the department and its faculty have major roles in the Center for Automation and Intelligent Systems Research and the Microfabrication Laboratory (MFL).
The Center for Automation and Intelligent Systems Research encompasses several manufacturing related laboratories supported in part by CAMP Inc. through the State of Ohio's Thomas Edison research center program. The CAISR laboratories are the Mechatronics Laboratory, Intelligent Systems Laboratory, Multimedia and Computations Intelligent Systems Laboratory and Control and Signal Processing Laboratories. These laboratories are equipped with a diverse range of modern scientific and CAD workstations, computer controlled robots, materials handling devices, image processing and computer vision systems. These laboratories support research activities in robotics, agile and flexible manufacturing, multimedia internet applications to manufacturing, rotating machinery diagnostics, optical sensing and process control.
The MFL, which includes a class 100 clean room, provides state-of-the-art facilities for device design, fabrication, and testing. The MFL supports a broad spectrum of micromachining processes, including bulk micromachining, surface micromachining, wafer bonding, and micromolding. These micromachining processing capabilities are augmented by a 2 micron CMOS process for the fabrication of integrated microsensor and microactuators. The MFL supports a broad range of research projects by investigators from a number of departments within the university.
Electrical Engineering and Applied Physics (EEAP)
EEAP 101, Introduction to Electrical Engineering, 3
The application of basic mathematics and physics to the solution of engineering problems. Topics will include: complex numbers and phasor representation of signals, basic vector and matrix manipulations and their applications to circuit analysis, image processing, visualization of vector fields, filtering and display of data, binary coding of information. Homework will be done on the computer using commercial engineering software.
Prerequisite: MATH 121 and concurrent MATH 122 and concurrent PHYS 120
EEAP 240, Electronic Circuits I, 4
A terminal course for non-electrical engineering students. Modeling and circuit analysis and concept in circuit anal sources, Kirchhoft's laws, Thevenin and Norton equivalents, operational amplifiers and applications, inductor and capacitors, sinusoidal steady state response of network, impedance, phasor notation, diode circuits, transistor small-signal model circuit, biasing consideration, frequency response amplifiers, introduction to digital elect circuits, practical application of electronics. Laboratory experiments stress measurements.
Prerequisite: MATH 122 and PHYS 120
EEAP 245, Electrical Circuits, Signals and Systems I, 4
Basic circuit analysis (Kirchoff's laws). Circuit elements (R, L, and C) and their terminal relations. Linearity and superposition. Simple op-amp circuits. First and second order circuit dynamics and the Laplace transform. The s-domain: pole-zero diagrams, time-domain design. Spice simulation. Introduction to diodes, BJT's, and FET's. Laboratory exercises, which provide reinforcement of the concepts are given concurrently.
Prerequisite: MATH 228 or MATH 224
EEAP 246, Electrical Circuits, Signals and Systems II, 4
BJT, diode, and FET circuit applications. The sinusoidal steady state and phasor analysis. Frequency domain considerations including Fourier series and Fourier transforms. Sampling theorem. The DFT. Bode plots and their relationship to the frequency domain representation of signals. Gain-bandwidth product, slewrate and other limitations of real devices. Filter design. Laboratory exercises which provide reinforcement of the concepts are given concurrently.
Prerequisite: EEAP 245
EEAP 282, Introduction to Microprocessors, 4
Representation of numbers and characters, stored program concepts, microcomputer architectures, memory, instruction timing and execution, machine language programming, instruction sets, addressing modes, indexing, subroutines and parameter passing, stack operations, interrupt handling, peripherals and support devices. Laboratory.
Prerequisite: CMPS 131
EEAP 290, Special Topics, 1-36
Limited to sophomores and juniors. Requires consent of instructor.
EEAP 309, Electromagnetic Fields I, 3
Maxwell's integral and differential equations, boundary conditions, constitutive relations, energy conservation and Poynting vector, wave equation, plane waves, propagating waves and transmission lines, characteristic impedance, reflection coefficient and standing wave ratio, in-depth analysis of coaxial and strip lines, electro and magnetoquasistatics, statics, simple boundary value problems, correspondence between fields and circuit concepts, energy and forces.
Prerequisite: MATH 223 and MATH 224 and PHYS 219
EEAP 310, Electromechanical Energy Conversion, 4
Electromechanical dynamics, modeling and control. Forces in quasistatic magnetic systems. Energy conversion properties of rotating machines. Analysis and control of dc servomotors, ac servomotors, reluctance machines, inductance machines, and magnetic bearing. Analysis of electromagnetic sensors. Electronic communication, torque linearization through computer controls and fluxvector control electromechanical properties are measured in the lab and high performance controls are constructed and tested.
Prerequisite: EEAP 309
EEAP 311, Electromagnetic Fields II, 4
Boundary value problems, guided electromagnetic waves, rectangular and circular waveguides, strip lines, losses in waveguiding structures, scattering, wave optics and wave propagation in anisotropic media, ferrites and plasmas, resonant systems, cavities, microwave network, multiports, scattering matrix formulation, radiation and antennas, radiation from dipoles, apertures, and simple arrays. Lab is project oriented; student required to develop computer solution to problems related to course material.
Prerequisite: EEAP 309 and CMPS 131
EEAP 321, Physical and Solid-state Electronics, 3
Quantum mechanics, energy bands and charge carries in semiconductors. Excess carriers in semiconductors. Principles of semiconductor devices that rely on the electrical properties of semiconductor surfaces and junctions. Development of equivalent circuit models and performance limitations of these devices. Devices covered include: junction, and bipolar transistors, Schottky junctions, mos capacitors, junction gate and mos field effect transistors, optical devices such as photodetectors, diodes, and solar cells.
Prerequisite: EMSE 314
EEAP 322, Integrated Circuits/Electronic Devices, 3
Technology of monolithic integrated circuits and devices, including crystal growth and doping, photolithography, vacuum technology, metalization, wet etching, thin film basics, oxidation, diffusion, ion implantation, epitaxy, chemical vapor deposition, plasma processing, and micromachining. Basics of semiconductor devices including junction diodes, bipolar junction transistors, and field effect transistors.
Prerequisite: EEAP 321
EEAP 344, Electronic Design, 3
The design and analysis of real-world circuits. Topics include: junction diodes, non-ideal op-amp models, characteristics and models for large and small signal operation of bipolar junction transistors (BJT's) and field effect transistors (FET's), selection of operating point and biasing for BJT and FET amplifiers. Hybrid-pi model and other advanced circuit models, cascaded amplifiers, negative feedback, differential amplifiers, oscillators, tuned circuits, and phase-locked loops. Computers will be extensively used to model circuits. Selected experiments and/or laboratory projects.
Prerequisite: EEAP 246
EEAP 345, Network Synthesis, 3
Design techniques for the construction of filters, delayors, predictors, analog computer networks, and necessary and sufficient requirements for the realization of practical networks.
Prerequisite: EEAP 246
EEAP 351, Communications and Signal Analysis, 3
Fourier transform analysis and signal sampling, reconstruction, and distortion. AM, FM, and SSB modulation and other modulation methods such as pulse code and delta modulation, pulse position, PSK, FKS, etc. Multiplexing, detection, and performance evaluation in terms of signal to noise ratio and bandwidth requirements.
Prerequisite: EEAP 246
EEAP 352, Digital Communications, 3
Fundamental bounds on transmission of information. Signal representation in vector space. Optimum reception. Probability and random processes with application to noise problems, speech encoding using linear prediction. Shaping of base-band signal spectra, correlative coding and equalization. Comparative analysis of digital modulation schemes. Concepts of information theory and coding. Applications to data communication.
Prerequisite: EEAP 351
EEAP 354, Antennas and Propagation, 3
Fundamentals of radiation, pattern, gain, basic antenna types, arrays, aperture antennas, receiving antennas, antennas over ground and interference effects. Antennas in communication. Radio wave propagation phenomena and their effect on communication systems: modes of propagation, atmospheric scattering, and attenuation.
Prerequisite: EEAP 311
EEAP 356, Microwave Engineering, 3
Transmission lines and circuit analysis, waveguides, modes of propagation, impedance matching techniques, scattering matrix, waveguide components, striplines, resonators, microwave theory, filters, microwave solid state devices.
Prerequisite: EEAP 311
EEAP 361, Lasers and Optics in Modern Electrical Engineering Systems, 3
Ray optics, ray matrices, and optical systems: diffraction effects; optical detectors; optical modulators; laser physics operations and characteristics of laser; fiber optics. Applications to communications and control systems.
Prerequisite: EEAP 309
EEAP 382, Microprocessor-based Design, 3
Microprocessor architectures, memory instruction timing and execution, interfacing, event-driven input/output, microprocessor support devices, integrated hardware/software design implementation.
Prerequisite: ECMP 280, EEAP 282
EEAP 383, Microprocessor Applications to Controls, 3
Digital control and its implementation using microprocessors. Z-transforms. Time response characteristics, steady-state error, mapping from the s-plane to the z-plane. Digital controller design-stability testing methods, gain and phase margins, pid controllers, digital filter structure.
Prerequisite: EEAP 246
EEAP 384, Digital Processing of Random Signals, 3
Discrete-time analysis and z-transforms. Discrete-time Fourier transform. Relationship between z-domain and frequency-domain. Review of probability density functions of multiple random variables. Stochastic processes. Correlation functions and power spectral density. Linear mean-square estimation. Optimal filters: wiener, recursive and matched filters. Gram-Schmidt orthogonalization and template matching.
Prerequisite: STAT 380 and EEAP 246
EEAP 396, Special Topics, 1-36
(Credit as arranged). Limited to juniors and seniors.
EEAP 397, Special Topics in Electrical Engineering, 1-36
(Credit as arranged) Limited to juniors and seniors. Requires consent of instructor.
EEAP 398, Senior Project in Electrical Engineering I, 4
EEAP 399, Senior Project in Electrical Engineering II, 4
Prerequisite: Concurrent EEAP 398
EEAP 412, Electromagnetic Fields III, 3
Maxwell's equations, macroscopic versus microscopic fields, field interaction with materials in terms of polarization vectors P and M. Laplace's and Poisson's equations and solutions, scalar and vector potentials. Wave propagation in various types of media such as anisotropic and gyrotropic media. Phase and group velocities, signal velocity and dispersion. Boundary value problems associated with wave-guide and carities. Wave solutions in cylindrical and spherical coordinates. Radiation and antennas.
EEAP 416, Ultrasonic Engineering, 3
Acoustical waves in fluids and solids, surface acoustic waves, transmission phenomena, radiators, transducers, filters, flow measurements, pulse echo techniques, flaw detection, sonar, imaging, holography.
EEAP 420, Solid State Electronics I, 3
Quantum mechanics and solid state physics. Crystal structures, electrons in periodic structures, band structures, transport phenomenon, nonequilibrium process, lattice dynamics, scattering mechanis, surface and interface physics; physics of semiconductor electronic devices.
Prerequisite: EEAP 321
EEAP 422, Solid State Electronics II, 3
Advanced physics of semiconductor devices. Review of current transport and semiconductor electronics. Surface and interface properties. P-N junction. Bipolar junction transistors, field effect transistors, solar cells and photonic devices.
Prerequisite: PHYS 481
EEAP 424, Integrated Circuit Technology I, 3
Review of semiconductor technology. Device fabrication processing, material evaluation, oxide passivation, pattern transfer technique, diffusion, ion implantation, metallization, probing, packaging, and testing. Design and fabrication of passive and active semi-conductor devices.
Prerequisite: EEAP 322
EEAP 426, MOS Integrated Circuit Design, 3
Design of digital and analog MOS integrated circuits. IC fabrication and device models. Logic, memory, and clock generation. Amplifiers, comparators, references, and switched-capacitor circuits. Characterization of circuit performance with/without parasitics using hand analysis and spice circuit simulation.
Prerequisite: EEAP 321 and EEAP 344 or equivalent
EEAP 431, Computer Processing of Images, 3
Introduction to computer vision methodologies. Includes the imaging systems: optics and detectors and geometric relationships between scene and image, 3-D scene scanning and imaging techniques including stereovision and laser rangefinders. Digital signal processing in 2-D and optical preprocessing of images. Real-time digital transmission of dynamic images and HDTV. Hardware issues in processing of vision information.
EEAP 432, Optical Communication, 3
In this course, suitable for graduate students or advanced undergraduates interested in photonics, a broad range of topics will be covered in the field of optical communication, with an aim to provide a sophisticated perspective of current technology and trends in optical communication components, systems, and networks.
Prerequisite: EEAP 309
EEAP 434, Microfabricated Silicon Electromechanical Systems, 3
Topics related to current research in microelectromechanical systems based upon silicon integrated circuit fabrication technology: fabrication, physics, devices, design, modeling, testing, and packaging. Bulk micromachining, surface micromachining, silicon to glass and silicon-silicon bonding. Principles of operation for microactuators and microcomponents. Testing and packaging issues.
Prerequisite: EEAP 322 or EEAP 424
EEAP 452, Random Signals, 3
Fundamental concepts in probability. Probability distribution and density functions. Random variables, functions of random variables, mean, variance, higher moments, Gaussian random variables, randon processes, stationary random processes, and ergodicity. Correlation functions and power spectral density. Orthogonal series representation of colored noise. Representation of bandpass noise and application to communication systems. Application to signals and noise in linear systems. Introduction to estimation, sampling, and prediction. Discussion of Poisson, Gaussian, and Markov processes.
EEAP 463, Research Topics in Lasers and Optics, 3
Topics related to current research, e.g., laser theory, coherent optics, optical information processing.
EEAP 483, Data Acquisition and Control, 3
Data acquisition (theory and practice), digital control of sampled data systems, stability tests, system simulation digital filter structure, finite word length effects, limit cycles, state-variable feedback and state estimation. Laboratory includes control algorithm programming done in assembly language.
EEAP 484, Computational Intelligence I, 3
This course is concerned with learning the fundamentals of a number of computational methodologies which are used in adaptive parallel distributed information processing. Such methodologies include neural net computing, evolutionary programming, genetic algorithms, fuzzy set theory, and "artificial life". These computational paradigms complement and supplement the traditional practices of pattern recognition and artificial intelligence. Functionalities covered include self organization, learning a model or supervised learning, optimization, and memorization.
EEAP 485, Computational Intelligence II, 3
This course is concerned with the combined use of the methods of computational intelligence in the performance of complex real-world tasks. Tasks considered include learning models of Ôopaque' systems, design and operation of fuzzy control systems, neural-net computing control of systems, optimal control, adaptive learning of time-variant time series, data compression, classification, self-organization of objects into categories, inductive reasoning, decision-making interpretation of signal and images.
Prerequisite: EEAP 484
EEAP 489, Robotics I, 3
Analysis of robot mechanical systems. Link relationships and frame assignment, coordinate transformations, forward and inverse kinematics and dynamical analysis. Planning of manipulator trajectories. Force, position, and hybrid control. Application of these techniques to selected industrial robots.
Prerequisite: EEAP 383 or EEAP 483
EEAP 491, Intelligent Systems I, 3
(Also listed as ECMP 491) Artificial intelligence and programming techniques used in design and implementation of intelligent systems. Problem solving and game playing by computer, different representation of problems and games, and their associated solution methods. Knowledge representation: logic, semantic networks frames. Programming in LISP and Prolog.
EEAP 500, Electrical Engineering and Applied Physics Colloquium, 0
Lecture program covering current research in various areas of electrical engineering. Attendance by graduate students required.
EEAP 526, Mixed-signal Systems, 3
Mixed-signal (analog/digital) integrated circuit design. D-to-A and A-to-D conversion, applications in mixed-signal VLSI, low-noise and low-power techniques, and communication sub-circuits. System simulation at the transistor and behavioral levels using SPICE. Class will design a mixed-signal CMOS IC for fabrication by MOSIS.
Prerequisites: EEAP 426 or consent of instructor.
EEAP 527, Advanced Sensors, 3
Sensor technology with a primary focus on semiconductor-based devices. Physical principles of energy conversion devices (sensors) with a review of relevant fundamentals: elasticity theory, fluid mechanics, silicon fabrication and micromachining technology, semiconductor device physics. Classification and terminology of sensors, defining and measuring sensor characteristics and performance, effect of the environment on sensors, predicting and controlling sensor error. Mechanical, acoustic, magnetic, thermal, radiation, chemical and biological sensors will be examined. Sensor packaging and sensor interface circuitry.
Prerequisites: Graduate standing. EEAP 322 or 424 and EEAP 434 are recommended.
EEAP 531, Computer Vision for Industrial Applications, 3
Methods of computer vision for scene interpretation, object recognition, and other applications of machine vision. Geometric optics, characteristics of sensors of many types, binary and gray scale imaging techniques, segmentation methods. Inspection of machined surfaces.
Prerequisite: EEAP 482 or EEAP 483
EEAP 580, Advanced Signal Processing, 3
Design and implementation of signal processing techniques such as linear prediction, adaptive filters, parametric signal modeling, spectral estimation; two-dimensional signal processing, specific subprojects assigned to each student.
EEAP 583, Implementation of Non-linear Control, 3
Nonlinear control with emphasis on applications. Basic theory including describing functions, equivalent gains, and Lyapunov stability. Emphasis on digital implementation of nonlinear controllers for high performance applications such as servomechanisms, manipulators, and aerospace systems. Comparison of nonlinear and linear designs. Laboratory experiments and CAD tools for controller performance verification.
EEAP 589, Robotics II, 3
Survey of research issues in robotics. Force control, visual servoing, robot autonomy, on-line planning, high-speed control, man/machine interfaces, robot learning, sensory processing for real-time control. Primarily a project-based lab course in which students design real-time software executing on multi-processors to control an industrial robot.
Prerequisite: EEAP 489
EEAP 600N, Special Topics, 1-36
EEAP 600P, Special Topics: Robotics, 3
EEAP 601, Independent Study, 1-36
Note that credits can be transferred to EEAP 701 only in the semester in which student advances to candidacy.
EEAP 649, Project M.S., 1-9
EEAP 651, Thesis M.S., 1-36
(Credit as arranged)
EEAP 701, Dissertation Ph.D., 1-36
(Credit as arranged)
BACHELOR OF SCIENCE IN ENGINEERING DEGREE
MAJOR IN ELECTRICAL ENGINEERING
Fall Semester | Class/Lab/Credit Hours | Spring Semester | Class/Lab/Credit Hours |
|
FRESHMAN |
| Open elective humanities/social science | (3-0-3) | Humanities/social science open elective | (3-0-3) |
| CHEM 107, Properties and Structure of Matter I | (3-0-3) | CHEM 108, Properties and Structure of Matter II | (3-0-3) |
| CMPS 131, Computer Programming | (2-2-3) | CHEM 113, Principles of Chemistry Laboratory | (1-3-2) |
| MATH 121, Calculus for Science and Engineering I | (4-0-4) | PHYS 121, General Physics I | (4-0-4) |
| ENGL 150, Expository Writing | (3-0-3) | MATH 122, Calculus for Science and Engineering II | (4-0-4) |
| PHED 101, Physical Education Activities | (0-3-0) | PHED 102, Physical Education Activities | (0-3-0) |
| Total | (15-5-16) | Total | (15-6-16) |
|
SOPHOMORE |
| Humanities/Social Science Sequence I | (3-0-3) | Humanities/Social Science Sequence II (3-0-3) |
| PHYS 122, General Physics II | (4-0-4) | PHYS 221, General Physics III | (3-0-3) |
| MATH 223, Calculus for Science and Engineering III | (3-0-3) | MATH 224, Elementary Differential Equations | (3-0-3) |
| ECMP 280, Digital Logic | (3-2-4) | EEAP 245, Electronic Circuits, Signals & Systems I | (3-2-4) |
| EEAP 282, Introduction to Microprocessors | (3-2-4) | STAT 380, Probability & Statistics | (3-0-3) |
| Total | (16-4-18) | Total | (15-2-16) |
|
JUNIOR |
| Humanities/Social Science Sequence II | (3-0-3) | Humanities/Social Science Sequence IV | (3-0-3) |
| EEAP 246, Electrical Circuits,Signals & Systems II | (3-2-4) | EEAP 321, Physical and Solid State Electronics | (3-0-3) |
| EEAP 309, Electromagnetic Fields I | (3-0-3) | EEAP 344, Electronic Circuit Design | (3-0-3) |
| EMSE 314, Electrical, Magnetic Optical Properties of Materials | (3-0-3) | Electrical Engineering Core Elective I | (3-2-4)2 |
| EEAP 384, Digital Processing of Random Signals | (3-0-3) | Engineering Core Elective I | (3-0-3)4 |
| | Approved Technical Elective | (3-0-3) |
| Total | (15-2-16) | Total | (18-2-19) |
|
SENIOR |
| Engineering Core Elective II | (3-0-3)5 | Humanities/Social Science Elective | (3-0-3) |
| EEAP 398, Senior Project Laboratory I | (0-8-4)6 | Open Humanities & Social Sciences Elective | (3-0-3)7 |
| ENGL 398, Professional Communications | (2-0-2) | EEAP 399, Senior Project Laboratory II | (0-8-4) |
| Open Elective | (3-0-3) | Approved Technical elective | (3-0-3)+ |
| Approved Technical elective | (3-0-3)+ | Open Elective | (3-0-3) |
| Total | (11-8-15) | Total | (12-8-16) |
Graduation Requirement: 132 hours total + graphics proficiency
2 Electrical Engineering core elective must be chosen from: EEAP 310 Electromechanical Energy Conversion, EEAP 311 Electromagnetic Fields II This is normally taken in the second semester of the junior year.
3 One Engineering Core elective must be chosen from one of the following three groups:
ECIV 110 Statics or EMAE 181 Dynamics; EIND 250 Production Systems Mgmt, EIND 352 Engineering Economics or OPRE 345 Decision Theory
EMAE 150 Thermodynamics
4 A second Engineering Core elective must be chosen from one of the same three groups; however, it cannot be from the same group as Engineering Core #1 and is normally taken in the senior year.
5 Co-op students can usually obtain credit for the first semester of Senior Project Lab by submitting a written report and doing an oral presentation on the student's design work. This is arranged through the senior project instructor.
6 If both electives in the Freshman year were Humanities/Social Science courses, this course may be an open elective.
+ The student will choose technical electives for purposes of specialization or development of breadth. Department approval for out of department courses must be obtained from the student's advisor.
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