Department of Electrical Engineering and Applied Physics
Glennan Building
Phone 368-4088; Fax 368-2668
Electrical engineering is a broad, dynamic field offering a great diversity of career opportunities in areas such as microwave and rf 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 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.
Sheldon Gruber, Sc.D. (Massachusetts Institute of Technology)
Professor
Signal processing, machine vision and industrial inspection
Dov Hazony, Ph.D. (University of California, Los Angeles)
Professor; Director, Hans Jaffe Ultrasonics Laboratory
Network synthesis; ultrasonics; communications
Wen H. Ko, Ph.D. (Case Institute of Technology)
Emeritus Professor
Solid state electronics; medical instrumentation microsensors and actuators; Micro-electro-mechanical systems and components
Mehran Mehregany, Ph.D. (Massachusetts Institute of Technology)
Assistant Professor
Solid-state sensors and actuators, microelectromechanical systems, and integrated circuits
Francis L. Merat, Ph.D. (Case Western Reserve University)
Associate Professor
Computer vision; industrial inspection; intelligent process planning and CAE systems; 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
Yoh-Han Pao, Ph.D. (Pennsylvania State University)
George S. Dively Distinguished Emeritus Professor of Engineering
Signal and image processing; pattern recognition; artificial intelligence; neural-net computing; automation
Stephen M. Phillips, Ph.D. (Stanford University)
Assistant Professor
Nonlinear and adaptive control; sampled-data and multi-mode control; computer aided control design and analysis.
Massood Tabib-Azar, Ph.D. (Rensselaer Polytechnic Institute)
Associate Professor
Electronic materials characterization; electronic devices.
Yoshiyasu Takefuju, Ph.D. (Keio University, Japan)
Associate Professor
Neural network architectures and applications to VLSI technology; multi-processor architectures.
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 adviser, 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.
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.
Undergraduate students who maintain at least a 3.0 grade point average may, with the consent of the faculty adviser, 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 243, Electronic Circuits Laboratory (3)
- EEAP 244, Electrical Circuits, Signals and Systems (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)
a MATH 121 and MATH 122 may be substituted for these courses.
b PHYS 120, PHYS 219, and PHYS 220 may be substituted for these courses.
Bachelor of Science in Engineering Degree
FRESHMAN
FALL SEMESTER
Open elective humanities/social science (3-0-3)
CHEM 105, Principles of Chemistry I (3-0-3) or
CHEM 107, Properties and Structure of Matter I (3-0-3)
CMPS 131, Computer Programming (2-2-3)
MATH 121, Calculus for Science and Engineering I (4-0-4)
ENGL 150, Expository Writing (3-0-3)
PHED 101, Physical Education Activities (0-3-0)
Total (15-5-16)
SPRING SEMESTER
Humanities/social science open elective (3-0-3)
CHEM 106, Principles of Chemistry II (3-0-3) or
CHEM 108, Properties and Structure of Matter II (3-0-3)
CHEM 113, Principles of Chemistry Laboratory (1-3-2)
MATH 122, Calculus for Science and Engineering II (4-0-4)
PHYS 120, General Physics I(1) (4-0-4)
PHED 102, Physical Education Activities (0-3-0)
Total (15-6-16)
SOPHOMORE
FALL SEMESTER
Humanities/Social Science Sequence I (3-0-3)
EEAP 282, Introduction to Microprocessors (3-2-4)
MATH 223, Calculus for Science and Engineering III (3-0-3)
PHYS 219, General Physics II (4-0-4)
Engineering Core Elective I(2) (3-0-3)
Total (16-2-17)
SPRING SEMESTER
ENGL 398, Professional Communication (2-0-2)
EEAP 243, Electronic Circuits/Signals Lab (2-2-3)
EEAP 244, Electronic Circuits, Signals & Systems (5-0-5)
MATH 224, Elementary Differential Equations (3-0-3)
PHYS 220, General Physics III (3-0-3)
Total (15-2-16)
JUNIOR
FALL SEMESTER
Math Elective(3) (3-0-3)
Humanities/Social Science Sequence II (3-0-3)
EEAP 309, Electromagnetic Fields I (3-0-3)
EEAP 383, Data Acquisition/Control (3-0-3)
ECMP 280, Digital Logic (3-2-4)
EMSE 314, Electrical, Magnetic Optical Properties of Materials (3-0-3)
Total (18-2-17)
SPRING SEMESTER
Humanities/Social Science Sequence III (3-0-3)
Electrical Engineering Core Elective I(4) (3-2-4)
EEAP 321, Physical and Solid State Electronics (3-0-3)
EEAP 344, Electronic Circuit Design (3-0-3)
Approved Technical Elective(+) (3-0-3)
Total (15-2-16)
SENIOR
FALL SEMESTER
Engineering Core Elective II5 (3-0-3)
Humanities/Social Science Sequence IV (3-0-3)
EEAP 398, Senior Project Laboratory I(6) (0-8-4)
Open Elective (3-0-3)
Approved Technical elective(+) (3-0-3)
Total (12-8-16)
SPRING SEMESTER
Humanities/Social Science Elective (3-0-3)
Open HM/SS Elective(7) (3-0-3)
EEAP 399, Senior Project Laboratory II (0-8-4)
Approved Technical elective(+) (3-0-3)
Open Elective (3-0-3)
Total (12-8-16)
Graduation Requirement: 131 hours total + graphics proficiency
1 Selected students may be invited to take PHYS 125, 126 in place of an open elective and PHYS 120.
2 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
This elective is normally taken in the first semester of the second year.
3 A mathematics elective elective must be chosen from:
- MATH 201 Intro. to Linear Algebra
- MATH 324 Intro. to Complex Analysis
- MATH 345 Intro. to Applied Mathematics
- STAT 385 Statistical Methods
This elective is normally taken in the first semester of the Junior year.
4 Electrical Engineering core elective must be chosen from:
- EEAP 310 Electromechanical Energy Conversion
- EEAP 311 Electronmagnetic Fields II
This is normally taken in the second semester of the Junior year.
+ 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 studentŐs advisor.
5 A second 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
This elective cannot be from the same group as Engr Core Elective I and is normally taken in the first semester of the Senior year.
6 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 studentŐs co-op work. This is arranged through the Senior project instructor.
7 If both electives in the Freshman year were Humanities/Social Science courses, this course may be an open elective.
GRADUATE PROGRAMS
The department offers graduate programs leading to the Master of Science and Doctor of Philosophy degrees. The programs are comprehensive and basic, emphasizing three major areas in which the faculty are actively engaged in research: solid state electronics; control, automation, and intelligent systems; and electromagnetic theory and wave propagation. 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 adviser'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 adviser, 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 adviser, 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. A second stage requires a research examination, taken not later than the end of the semester of first Ph.D. dissertation registration, which is often a thesis proposal which assesses preparation for research at the Ph.D. level. 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.
Solid State Electronics
Research includes: design, fabrication and testing of solid state electronic devices and integrated circuits; semiconductor physical and chemical sensor development; design, modeling, fabrication and testing of microsensors, microactuators, micro-opto mechanical devices, and microelectromechanical systems.
Control, Automation, and Intelligent Systems
Research activities include image processing; neural network applications; pattern recognition; artificial intelligence; process automation; intelligent machine tool control; in-process gauging and control; adaptive learning methods applicable to robotics; the application of artificial intelligence to robotic systems and manufacturing; and compliant control of robotic systems; noncontact. Inspection of production quality; machine vision for robotic applications.
Electromagnetic Waves and Wave Propagation
Research activities include, electromagnetic propagation and scattering, and applications of ultrasonics.
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 24 basic low frequency work stations; the Lester J. Kern Computational Laboratory, with 12 Hewlett-Packard Unix workstations, 7 in-circuit emulators and logic analyzers, Electromechanical Energy Conversion Laboratory, with four computer-controlled experimental stations; and the Advanced Electronic Device Laboratory (funded by the National Science Foundation) with light computer controlled device characterization benches. 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 Case Personal Computer Laboratory, which houses a variety of current small computers, which includes 486 based PCs and Macintosh IIs.
Research laboratories within the department include a Neural Network Computation Facility, the Hans Jaffe Ultrasonic Laboratory, with facilities for basic research in acoustics and ultrasonic waves; a Micro-Opto Mechanical Devices Laboratory with lasers and optical instrumentation; the Mechatronics Laboratory with a large range of robots and computer facilities; and the Control and Communications Laboratory, with computers and instrumentation for control and signal processing. In addition, the department and its faculty have major roles in the Center for Automation and Intelligent Systems Research, the Electronics Design Center, and the Polymer Microdevice Laboratory. The Center for Automation and Intelligent Systems Research is equipped with a diverse range of modern workstations, intelligent graphics terminals, and other high quality research type data acquisition peripherals such as frame grabbers and image processors. The Electronics Design Center incorporates a state of the art microfabrication facility for four inch wafer processing which includes a class 100 clean room and the equipment for the basic processing steps, diffusion, LPCVD/CVD, photolithography, wet etching, dry etching and metalization for the fabrication of microsensors and microactuators as well as LSI electronics. It has extensive device testing facilities, and advanced work stations for design and modeling. The Polymer Microdevice Laboratory is a clean room facility with equipment for production of monolayer polymer films and for fabrication of semiconductor devices using polymer insulating layers. Department faculty and students also have access to the facilities the National Submicron Facility at Cornell 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 is done on the computer using MatLab. Prerequisite: MATH 122 and PHYS 120, CMPS 131 or any other programming course.
EEAP 240. Electronic Circuits (4).
A terminal course for non-electrical engineering students. Modelling and circuit analysis. Fundamental concepts in circuit analysis sources, Kirchhoft's laws, Thevenin and Norton equivalents, operational amplifiers and applications, inductors and capacitors, sinusoidal steady state response of networks, impedance and phasor notation, diode circuits, transistor small-signal models and circuits, biasing considerations, frequency response of amplifiers, introduction to digital electronic circuits, practical applications of electronics. Laboratory experiments stress measurements. Prerequisites: MATH 122, and PHYS 120 or equivalent. Students enrolling as specified in their curricula have priority.
EEAP-243. Electronic Circuits Laboratory (3).
A laboratory course based on the material in EEAP 244. Computer modeling of circuits and systems, Simulation labs will be based upon PSpice and MATLAB. Laboratory experiments will be done to verify computer simulations. Prerequisites: EEAP 244. (must be taken concurrently)
EEAP 244. Electronic Circuits and Systems (5).
Concepts of active and passive circuits and their responses to dynamic signals. Introduction to devices and models. An introduction to linear circuit analysis including: models for circuit elements, Ohm's and Kirchoff's laws, nodal and loop analysis, linearity, superposition, source transformations, Thevenin's and Norton's theorems, capacitors and inductors, RL and RC circuits, RLC circuits, sinusoidal excitation, phasors, impedance, complex frequency, amplifier frequency response with Bode plots, filters, resonant circuits, two-port networks. Linearity, superposition, signals in time and frequency domain. Analysis of transient circuit behavior. Laplace and Fourier transforms. Feedback and stability, pole-zero concepts. Prerequisites: MATH 224 and EEAP 243 Concurrently
EEAP 280. Digital Logic Design (3).
See ECMP 280.
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. Prerequisites: CMPS 131 or equivalent.
EEAP 290. Special Topics (1-3).
Limited to sophomores and juniors. Prerequisite: Consent of instructor.
EEAP 309. Electromagnetic Fields I (5).
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. Prerequisites: MATH 223, 224, and PHYS 219.
EEAP 310. Electromechanical Energy Conversion (4).
Electromechanical dynamics, modeling and control. Forces in quasi-static magnetic systems. Energy conversion properties of rotating machines. Analysis and control of dc servomotors, ac servomotors, reluctance machines, inductance machines, and magnetic bearings. Analysis of electromagnetic sensors. Electronic commutation, torque linearization through computer controls and flux-vector 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 wave-guiding structures, radiation and antennas, radiation from dipoles, apertures, and simple arrays. Laboratory is project oriented; students required to develop computer-based solutions 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 carriers in semiconductors. Excess carries 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, 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 Circuit Fabrication Technology (3).
Technology of monolithic integrated circuits and devices,including crystal growth and doping, photolithography, vacuum technology, metallization, wet etching, thin film basics, oxidation, diffusion, ion implantation, epitaxy, chemical vapor deposition, plasma processing, and fabrication processes for electronic devices and integrated circuits. Laboratory fabrication and actual testing of electronic devices. 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 (BJTs) and field effect transistors (FETs), 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. Prerequisites: EEAP 244, EEAP 243
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 amplitude and pulse position, PSK, FKS, etc., multiplexing, detection, and performance evaluation in terms of signal-to-noise ratio and bandwidth requirements. Prerequisites: EEAP 243 and EEAP 244.
EEAP 352. Digital Communication (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 baseband signal spectra, correlative coding and equalization. Comparative analysis of digital modulation scheme. Concepts of information theory and coding. Applications to data communication. Prerequisite: EEAP 351.
EEAP 354. Antennas and Propagation (3).
Fundamentals of radiation, pattern, pin, 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, waveguide, modes of propagation, impedance matching techniques, scattering matrix, waveguide components, stripline, resonators, microwave theory, filters, microwave solid state devices. Prerequisite: EEAP 311.
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. Prerequisites: EEAP 244 and EEAP 282.
EEAP 383. Microprocessor Applications to Control (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 structures. Limited enrollment. Prerequisites: EEAP 282.
EEAP 396. Special Topics in Electrical Engineering (credit as arranged).
Limited to juniors and seniors.
EEAP 397. Special Topics in Electrical Engineering (credit as arranged).
Limited to juniors and seniors. Requires consent of instructor.
EEAP 398. Senior Project in Electrical Engineering (4).
EEAP 399. Senior Project in Electrical Engineering (4).
* Undergraduate students with a grade point average of 3.0 or above may request permission to enroll in selected graduate courses. Where enrollment is limited, EEAP graduate students have priority. Not all listed courses are offered every year.
EEAP 412. Electromagnetic Fields III (3).
Maxwell's equations, macroscopic versus microscopic fields, field interaction with materials in terms of polarization vectors, 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 waveguides and cavities. 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, fault detection, non-destructive testing, sonar, imaging.
EEAP 420. Solid State Electronics I (3).
Quantum mechanics and solid state physics. Crystal structure, electrons in periodic structure. Band structures. Transport phenomenon. Non-equilibrium processes. Lattice dynamics. Scattering mechanism. Surface and interface physics; Physics of semiconductor electronic devices.
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. Junction and MOS field effect transistors. Solar cells and photonic devices.
EEAP 424. Integrated Circuit Technology I (3).
Review of semiconductor technology. Device fabrication processing, material evaluation, oxide passivation, pattern transfer techniques, diffusion, ion implantation, metallization, probing, packaging, and testing. Design and fabrication of passive and active semiconductor devices.
EEAP 426. Design of MOS Integrated Circuits (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. Prerequisites: EEAP 321 and 344 or similar background in MOS device physics and transistor circuit design.
EEAP 431. Computer Processing of Images (3).
Introduction to computer vision methodologies. Include 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. Prerequisites: EEAP 244, 383 or equivalent.
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-to-silicon bonding. Principles of operation for microactuators and microcomponents. Testing and packaging issues. Prerequisite: EEAP 322 or 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, random 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. Applications to signals and noise in linear systems. Introduction to estimation, sampling, and prediction. Discussion of Poisson, Gaussian, and Markov processes.
EEAP 482. Multiprocessing and Special Architectures (4).
Advanced digital/analog processing systems. Problem representations, modeling, and simulation of massively parallel processing systems based on cellular architectures, fuzzy computer architectures, and neural network architectures. Technology topics such as VLSI design problems, molecular biology problems, game theory problems, and management science.
EEAP 483. Data Acquisition and Control (3).
Data acquisition (theory and practice), digital control of sampled data systems, stability tests, system simulation digital filter structures, finite word length effects, limit cycles, state-variable feedback and state estimation. Laboratory includes control algorithm programming done in assembly language.
EEAP 484. Adaptive Pattern Recognition and Neural Networks (3).
This course introduces and relates the basic concepts of pattern recognition and neural networks. A current and coherent view of pattern recognition: adaptive pattern recognition implemented in neural networks which are elemental processors connected like their biological models. Focus is on the generic issues of algorithms with insights provided by current research; dealing with structure in patterns; dynamics of neural networks: degrees of belief; concept of neural controllers; integration of symbolic processing with neural network processing. Prerequisite: Consent of instructor or graduate standing.
EEAP 485. Use of Neurocomputing (3).
In this course we identify the function-alities attainable with known forms of artificial neural networks and examine the various manners in which these capabilities are or might be used in information processing. Tasks examined include: classification, estimation, system identification, signal and image processing, adaptive controls, knowledge representation and formation of memory. Prerequisite: EEAP 484 or equivalent.
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. Co or 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. Prerequisite: CMPS 131.
EEAP 500. Electrical Engineering and Applied Physics Colloquium (0).
Lecture program covering current research in various areas of electrical engineering. Attendance by resident graduate students required.
EEAP 521. Solid State Electronics III (3).
Research topics in solid state electronics related to current research, e.g., computer-aided design modeling and fabrication, high frequency and switching device, novel materials including superlattices, semiconductor sensors, electronic materials, microwave devices, and integrated circuits.
EEAP 523. Advanced Physical and Solid State Electronics I (3).
Research topics on the state of the art in solid-state materials and device. Topics may include: solid state sensors and their technology, sub-micron silicon MOSFETS, special silicon bipolar transistors, III-V compound semiconductor materials, III-V compound MESFETS, heterojunction bipolar transistors (HBT), superlattices, quantum well and resonant tunneling devices, superconductive devices, and optoelectronic devices. Prerequisite: EEAP 422.
EEAP 525. Integrated Circuit Technology III (3).
Advanced fabrication techniques including ion implanting, MBE, CVD epitaxial growth, plasma etching, and deposition. Analytical methods for material and integrated circuits evaluation. X-ray crystallography, electron microscopes, electron microprobes, scanning Auger analysis, oxide and metal oxide evaluation techniques, laboratory projects. Prerequisite: EEAP 426.
EEAP 531. Computer Vision with Industrial Applications (3).
Geometric optics, ray matrices, calibration of monocular and stereo imaging systems. Adaptive camera thresholding and image segmentation, morphological and convolutional image processing. Selected topics including edge estimation and industrial inspection, optimal filtering, model matching, CAD-based vision, and range image processing. Neural-net image processing. Model-based computer vision for scene interpretation and autonomous systems. Prerequisites: EEAP 431 and EEAP 489 are recommended but not required
EEAP 580. Advanced Digital 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 582. VLSI (Silicon) Neural Networks (3).
Characteristics, theory and silicon design of deterministic and stochastic neural networks (Boltzmann, Gaussian, and Cauchy machines), variable synaptic interconnection, variable-gain sigmoid neurons for NP-complete optimization problems. Projects involving design and testing of silicon implementations based on CMOS technology through the NSF/MOSIS program. Prerequisite: EEAP 482 or consent.
EEAP 583. Implementation of Nonlinear Control (3).
Nonlinear control with emphasis on applications. Basic theory including describing functions, equivalent pins, 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 a multiprocessor to control an industrial robot. Prerequisite: EEAP 489.
EEAP 591. Intelligent Systems II (3).
This course addresses advanced topics in Artificial Intelligence including game playing, planning, understanding, natural language processing and learning. There is also emphasis on the role of memory in planning and in task performance. The role of neural-net computing (or connectionist models) is also examined. Prerequisite: EEAP 491; a knowledge of basic AI material such as symbolic expression processing, search and knowledge representation is helpful.
EEAP 600. Special Topics in Electrical Engineering and Applied Physics (credit as arranged).
Prerequisite: Graduate standing.
EEAP 601. Independent Study (credit as arranged).
Note that credits can be transferred to EEAP 701 only in the semester in which student advances to candidacy.
EEAP 623. Advanced Physical and Solid State Electronics II (3).
Research topics.
EEAP 651. Thesis (M.S.) (credit as arranged).
EEAP 701. Dissertation (Ph.D.) (credit as arranged).
Prerequisite: Completion of Ph.D. candidacy requirements.
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