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EE 507 - (3) (SI)
Analog Integrated Circuits
Prerequisite: EE 305, Corequisite: EE 402 or equivalent
Design of analog integrated circuits using Computer-Aided-Design
techniques. Verification of performance is obtained by building
and testing circuits where feasible, and by simulation.
EE 525 - (3) (Y)
Introduction to Robotics
Prerequisite: EE 402 or EE 621, or equivalent
Basic concepts of manipulator robot design, operation, and control:
kinematics (direct and inverse solution of the kinematic equations),
dynamics, and control (path, velocity, and force). Force, pressure,
and proximity sensors. Introduction to machine vision applied
to robotics. Students will work with small manipulator arms in
the lab.
EE 541 - (3) (Y)
Optics and Lasers
Prerequisites: EE 303, 309, 323
Review of the electromagnetic principles of optics. Maxwell's
equations. Reflection and transmission of electromagnetic fields
at dielectric interfaces. Glaussian beams. Interference and diffraction.
Laser theory with illustrations chosen from atomic, gas and semiconductor
laser systems. Detectors: photomultipliers and semiconductor-based
detectors. Noise theory and noise sources in optical detection.
EE 556 - (3) (Y)
Microwave Engineering I
Prerequisite: EE 309 or permission of instructor
Design and analysis of passive microwave circuits. Topics include
transmission lines, electromagnetic field theory, waveguides,
microwave network analysis and signal flow graphs, impedance matching
and tuning, resonators, power dividers and directional couplers,
and microwave filters.
EE 563 - (3) (Y)
Introduction to VLSI
Prerequisites: ENGR 208, EE 204, EE 303
NMOS and PMOS transistor design, CMOS fabrication, fabrication
design rules, inverter design, cell design using computer aided
design tool MAGIC, chip layout and design, VLSI circuit design
and implementation using the MOSIS process.
EE 564 - (3) (Y)
Microelectronic Integrated Circuit Fabrication
Prerequisite: EE 303 or permission of instructor
Semiconductor Device design and fabrication technology. The technology
portion discusses the fabrication techniques applicable to VLSI
circuits: silicon single crystal growth, oxidation, diffusion,
ion implantation epitaxy, metalization, etching and lithographic
processes. Device design centers on MOS theory and technologies
including derivation of circuit models and optimization considering
the constraints presented by materials, and fabrication technologies.
EE 576 - (3) (Y)
Digital Signal Processing
Prerequisites: EE 323, EE 324 or equivalent
The fundamentals of discrete-time signal processing are presented.
Topics include discrete-time linear systems, z-transforms, the
DFT and FFT algorithms, and digital filter design. Problem-solving
using the computer will be stressed.
EE 586/587 - (1-3) (SI)
Special Topics in Electrical Engineering
Prerequisite: Permission of instructor
A first-level graduate/advanced undergraduate course covering
a topic not normally covered in the course offerings. The topic
usually reflects new developments in the electrical and computer
engineering field. Offering is based on student and faculty interests.
EE 601 - (3) (SI)
Electric Network Analysis and Synthesis
Prerequisite: EE 204 and EE 324 or equivalent
Network topology; matrix models of network; network properties
(one-port, two-port and general) relevant to synthesis; synthesis
of driving-point immittances; approximation and synthesis of filters
(passive filters and active R-C filters).
EE 602 - (3) (SI)
Electronic Systems
Prerequisite: EE 204/307 or equivalent
Frequency response and stability of feedback electronic circuits.
Analysis and design of analog integrated circuits such as operational
amplifiers, multipliers, phase locked loops, A/D and D/A converters
and their application to instrumentation, control, etc.
EE 611 - (3) (Y)
Probability and Stochastic Processes
Prerequisites: APMA 310, Math 311, or equivalent
The purpose of this course is to introduce those concepts of probability
and stochastic processes frequently encountered in the fields
of systems analysis, communications and control. Major topics
covered include: probability theory, stochastic processes (stationarity,
ergodicity, Karhunen-Loeve expansion), linear system response
to stochastic processes, Gaussian processes, and Markov processes.
Emphasis will be placed on rigorous development and application
of the theory to problems in communication and control.
EE 613 - (3) (Y)
Communication Systems Engineering
Prerequisite: Undergraduate course in probability
A first graduate course in principles of communications engineering.
Course topics include a brief review of random process theory,
principles of optimum receiver design for discrete and continuous
messages, matched filters and correlation receivers, signal design,
error performance for various signal geometries, M-ary signaling,
linear and nonlinear analog modulation, and quantization. The
course will also treat aspects of system design such as propagation,
link power calculations, noise models, RF components, and antennas.
EE 614 - (3) (Y)
Estimation Theory
Prerequisite: EE 611 or permission of instructor
This course presents estimation theory from a discrete-time viewpoint.
One half of the course is devoted to parameter estimation, and
the other half to state estimation using Kalman filtering. The
presentation blends theory with applications, and provides the
fundamental properties of and interrelationships among basic estimation
theory algorithms. Although the algorithms are presented as a
neutral adjunct to signal processing, the material is also appropriate
for students with interests in pattern recognition, communications,
controls, and related engineering fields.
EE 621 - (3) (Y)
Linear Automatic Control Systems
Prerequisite: EE 324 or permission of instructor
Provides a working knowledge of the analysis and design of linear
automatic control systems using classical methods. Introduces
state space techniques. Dynamic models of mechanical, electrical,
hydraulic and other systems. Transfer functions. Block Diagrams.
Stability of linear systems: Nyquist criterion. Frequency response
methods of feedback systems design: Bode diagram. Root locus method.
System design to satisfy specifications. PID controllers; compensation
using Bode plots and the root locus. Powerful software is used
for system design.
EE 631 - (3) (Y)
Advanced Switching Theory
Prerequisite: ENGR 208 or equivalent
Review of Boolean Algebra; synchronous and asynchronous machine
synthesis; functional decomposition; fault location and detection;
design for testability techniques.
EE 635 - (3) (Y)
Computer Graphics in Engineering Design
Prerequisite: Knowledge of C
Display devices, line and circle generators; clipping and windowing;
data structures; 2D picture transformations; hidden line and surface
algorithm; shading algorithms; free form surfaces; color graphics;
3D picture transformation. Cross-listed as CS 645.
EE 642 - (3) (Y)
Optics for Optoelectronics
Prerequisite: EE 541 or permission of instructor
Covers the electromagnetic applications of Maxwell's equations
in photonic devices such as the dielectric waveguide, fiber optic
waveguide and Bragg optical scattering devices. Includes the discussion
of the exchange of electromagnetic energy between adjacent guides,
i.e., mode coupling. Ends with an introduction to nonlinear optics.
Examples of optical nonlinearity include second harmonic generation
and soliton waves.
EE 652 - (1 1/2) (Y)
Microwave Engineering Laboratory
Corequisite: EE 556 or permission of instructor
Measurement and behavior of high-frequency circuits and components.
Equivalent circuit models for lumped elements. Measurement of
standing waves, power, and frequency. Use of vector network analyzers
and spectrum analyzers. Computer-aided design, fabrication, and
characterization of microstrip circuits.
EE 655 - (3) (E)
Microwave Engineering II
Prerequisite: EE 556 or permission of instructor
Theory and design of active microwave circuits. Begins with a
review of signal flow graphs and matching networks. Major topics
include noise in two- port networks, video detectors and bolometers,
single-ended and balanced microwave mixers, low-noise microwave
amplifiers, oscillators, and injection- locking and nonlinear
effects. Selected topics from the literature such as power-combining
and quasi-optical arrays also are discussed.
EE 663 - (3) (Y)
Solid State Devices
Prerequisite: EE 303 or permission of instructor
Introduces semiconductor device operation by way of energy bands
and charge carrier statistics. Reviews operation of p-n and metal-semiconductor
junction characteristics for use in analysis of currently important
devices including: photoresistive sensors, thermistors, solar
cells, bipolar junction transistors and field effect transistors.
EE 666 - (1 1/2) (Y)
Microelectronic Integrated Circuit Fabrication Laboratory
Corequisite: EE 564
Determination of semiconductor material parameters: crystal orientation,
type, resistivity, layer thickness, and majority carrier concentration.
Silicon device fabrication and analysis techniques: thermal oxidation,
oxide masking, solid state diffusion of intentional impurities,
metal electrode evaporation, layer thickness determination by
surface profiling and optical interferometer. MOS capacitor design
and fabrication using the above techniques, characterization,
and verification of design models used.
EE 667 - (3) (Y)
Semiconductor Materials and Devices
Prerequisite: EE 303 or permission of instructor
This course discusses materials characterization of the elemental
semiconductors (Silicon and Germanium) and the relation of semiconductor
properties to the device structure and performance of discrete
devices and integrated circuits. Subjects covered include a review
of semiconductor principles, phase equilibria diagrams, semiconductor
purification, crystal imperfections, and crystal growth techniques.
Selected tutorial lectures on current industrial applications
of semiconductor technology will also be presented. Cross-listed
as MS 667.
EE 682 - (3) (Y)
Digital Picture Processing
Prerequisite: Graduate standing
Basic concepts of image formation and image analysis: imaging
geometries, sampling, filtering, edge detection, Hough transforms,
region extraction and representation, extracting and modeling
three-dimension objects. Students will be assigned analytical
and programming assignments to explore these concepts. Cross-listed
as CS 682.
EE 686/687 - (3) (SI)
Special Topics in Electrical Engineering
Prerequisite: Permission of instructor
A first-level graduate course covering a topic not normally covered
in the graduate course offerings. The topic will usually reflect
new developments in the electrical and computer engineering field.
Offering is based on student and faculty interests.
EE 693 - (3) (S)
Independent Study
Detailed study of graduate course material on an independent
basis under the guidance of a faculty member.
EE 695 - (3-6) (S)
Supervised Project Research
Formal record of student commitment to project research
under the guidance of a faculty advisor. A project report is required
at the completion of each semester. Registration may be repeated
as necessary.
EE 712 - (3) (Y)
Digital Communications
Prerequisite: EE 611
An in-depth treatment of digital communications techniques and
performance. Topics include performance of uncoded systems such
as Mary, PSK, FSK, and multi-level signaling; orthogonal and bi-orthogonal
codes; block and convolutional coding with algebraic and maximum
likelihood decoding; burst correcting codes; efficiency and bandwidth;
synchronization for carrier reference and bit timing; baseband
signaling techniques; intersymbol interference; and equalization.
EE 715 - (3) (O)
Performance Analysis of Communication Networks
Prerequisite: EE 611 or permission of instructor
Topologies arising in communication networks; queuing theory;
Markov Chains and ergodicity conditions; theory of regenerative
processes; routing algorithms; multiple-access and random-access
transmission algorithms; mathematical methodologies for throughput
and delay analyses and evaluations; performance evaluation; performance
monitoring; local area networks (LANs); interactive LANs; multimedia
and ATM networks. Cross-listed as CS 715.
EE 717 - (3) (Y)
Information Theory and Coding
Prerequisite: EE 611 or permission of instructor
A comprehensive treatment of information theory and its application
to channel coding and source coding. Topics include the nature
of information and its mathematical description for discrete and
continuous sources; noiseless coding for a discrete source; channel
capacity and channel coding theorems of Shannon; error correcting
codes; introduction to rate distortion theory and practice of
data compression; information and statistical measures.
EE 722 - (3) (Y)
Robotics
Prerequisites: EE 525, EE 621 or permission of instructor
Kinematics of manipulator robots in terms of homogeneous matrices,
solution of the kinematics equations; differential translations
and rotations, the Jacobian and the inverse Jacobian; manipulator
path control; manipulator dynamics, the Lagrange's and Newton's
formulations; manipulator control; principles of machine vision
applied to robots, sensors, edge and feature detection, object
location and recognition; stereo vision and ranging; programming
of robot tasks.
EE 724 - (3) (Y)
Modern Control Theory
Prerequisites: APMA 615, EE 621, or permission of instructor
A study of linear dynamical systems emphasizing canonical representation
and decomposition, state representation, controllability, observability,
normal systems, state feedback and the decoupling problem. Representative
physical examples. Cross-listed as MAE 752.
EE 726 - (3) (O)
Nonlinear Control Systems
Prerequisites: EE 621 and EE 724
Dynamic response of nonlinear systems; analysis of nonlinear systems
using approximate analytical methods; stability analysis using
the second method of Liapunov, describing functions and other
methods. Selected topics such as adaptive, neural and switched
systems. Introduction to the current literature. Cross-listed
as MAE 756.
EE 728 - (3) (E)
Digital Control Systems
Prerequisites: EE 621, EE 412, APMA 615 or equivalent
Sampling processes and theorems, z-transforms, modified transforms,
transfer functions, and stability criteria. Analysis in frequency
and time domains. Discrete state models of systems containing
digital computers. Some class time is devoted to experimental
work using small computers to control dynamic processes. Cross-listed
as MAE 854.
EE 734 - (3) (Y)
Reliable Digital Design and Analysis
Prerequisite: EE 631 or permission of instructor
This course covers techniques for designing and analyzing reliable
digital systems. The topics covered include fault models and effects,
fault avoidance techniques, hardware redundancy, error detecting
and correcting codes, time redundancy, software redundancy, combinatorial
reliability modeling, Markov reliability modeling, availability
modeling, maintainability modeling, trade-off analysis, and the
testing of redundant digital systems.
EE 735 - (3) (Y)
Digital and Computer System Design
Prerequisite: EE 435 or equivalent
Design of the elements of special purpose and large scale digital
processors using a hardware description language. Selected topics
from the literature.
EE 736 - (3) (Y)
Advanced VLSI Systems Design
Prerequisite: EE 563 or permission of instructor
Course topics include structured VLSI design, special purpose
VLSI architectures, and algorithms for VLSI computer-aided design.
A significant portion of the course is taken up with the design
and implementation of a large project. Also, papers from the current
literature are used as appropriate.
EE 741 - (3) (SI)
Fourier Optics
Prerequisite: EE 324 and EE 541 or permission of instructor
Presents the fundamental principles of optical signal processing.
Begins with an introduction to two-dimensional spatial, linear
systems analysis using Fourier techniques. Includes scalar diffraction
theory, Fourier transforming and imaging properties of lenses
and the theory optical coherence. Applications of Wavefront-reconstruction
techniques in imaging. Applications of Fourier Optics to analog
optical computing.
EE 753 - (3) (O)
Electromagnetic Field Theory
Prerequisite: EE 309 or equivalent. Suggested preparation
EE 556
Maxwell's equations applied to the general development of boundary
value problems, transmission systems, radiation, optics, plasmas
and other material media.
EE 757 - (3) (Y)
Computer Networks
Prerequisite: CS 656 or permission of instructor
Network topologies; backbone design; performance and queuing theory;
data-grams and virtual circuits; technology issues; layered architectures;
standards; survey of commercial networks, local area networks,
and contention-based communication protocols; encryption; security.
Cross-listed as CS 757.
EE 763 - (3) (Y)
Physics of Semiconductors
Prerequisite: EE 663 or permission of instructor
Semiconductor band theory, constant energy surfaces and effective
mass concepts. Statistics treating normal and degenerate materials,
spin degeneracy in impurities, excited impurity states and impurity
recombination. Carrier transport, scattering mechanisms, and prediction
techniques.
EE 768 - (3) (Y)
Semiconductor Materials
and Characterization Techniques
Prerequisite: EE 663 or permission of instructor
Semiconductor growth and characterization methods applicable to
III-V heteroepitaxial growth along with etching and contact formation
mechanisms. Physical, structural, and electrical characterization
tools including X-ray diffraction, Auger, Hall and C(V).
EE 774 - (3) (E)
Advanced Digital Signal Processing
Prerequisite: EE 576 or equivalent
Course topics will include application of discrete-time random
processes to discrete-time systems, effects of finite word length
in discrete-time processing, power spectrum estimation, multirate
digital signal processing, digital system design concepts, digital
system performance estimation, and other advanced topics such
as lattice filters.
EE 776 - (3) (O)
Multi-Dimensional and Array Signal
Processing
Prerequisites: EE 576 or permission of instructor
This course provides the basic background of multi-dimensional
digital signal processing with an emphasis on the differences
and similarities between the one-dimensional and multi-dimensional
cases. Topics include 2-D Fourier analysis, 2-D stability, 2-D
spectral estimation, and inverse problems such as beamforming
and reconstruction from projections. The theory developed serves
as the foundation of digital image processing, and is applied
to array signal processing (e.g., radar, sonar, seismic, medical,
and astronomical data processing).
EE 781 - (3) (Y)
Pattern Recognition
Prerequisite: EE 611 or equivalent
Feature extraction and classification concepts: Decision surfaces,
discriminant functions, Potential functions, Deterministic methods,
Automatic training of classifiers, Analysis of training algorithms
and classifier performance, Statistical classification: Optimality
and design of optimal decision rules, Clustering and Non-supervised
learning, Feature Selection and Dimensionality Reduction. Homework
assignments will include programming as well as analytical problem
sets. A final computer project will be assigned.
EE 782 - (3) (Y)
Advanced Computer Vision
Prerequisite: EE 682
Advanced topics in automated reconstruction of imaged objects
and computer interpretation of imaged scenes. Techniques for three-dimensional
object reconstruction. Computing motion parameters from sequences
of images. Computational frameworks for vision tasks such as regularization,
and stochastic relaxation. Approaches for autonomous navigation.
Depth image analysis. Novel imaging techniques and applications.
Parallel architectures for computer vision. Cross-listed as CS
782.
EE 786/787 - (3) (SI)
Special Topics in Electrical Engineering
Prerequisite: Permission of instructor
A first level graduate course covering a topic not normally covered
in the graduate course offerings. The topic will usually reflect
new developments in the electrical and computer engineering field.
Offering is based on student and faculty interests.
EE 793 - (3) (S)
Independent Study
Detailed study of graduate course material on an independent
basis under the guidance of a faculty member.
EE 814 - (3) (Y)
Advanced Detection and Estimation
Prerequisite: EE 611 or permission of instructor
Classical detection theory and hypothesis testing, (Bayes, Neymon-Pearson,
minimax), robust hypothesis testing, decision criteria, sequential
and nonparametric detection. Classical estimation theory (Bayes,
minimax, maximum likelihood), performance bounds, robust-outlier
resistant estimation of location parameters, stochastic distance
measures, parametric and robust operations in time series. (Prediction,
interpolation, filtering). Applications to problems in communications,
control, pattern recognition, signal processing. Cross-listed
as MATH 814.
EE 815 - (3) (Y)
Special Topics in Communications
Prerequisite: Permission of instructor
A variable content course addressing specific areas of interest
to students. Possible course topics include optical communication;
computer networks, satellite communications systems; phase lock
loop theory; advanced signal processing devices; advanced stochastic
processes and martingale theory; advanced detection; and estimation
theory.
EE 823 - (3) (O)
Optimal Control Systems
Prerequisite: EE 724 or permission of instructor
Development and utilization of Pontryagin's maximum principle,
the calculus of variations, Hamilton-Jacobi theory and dynamic
programming in solving optimal control problems. Performance criteria
including time, fuel, and energy. Optimal regulators and trackers
for quadratic cost index designed via the Ricatti equation. Introduction
to numerical optimization techniques. Cross-listed as MAE 853.
EE 825 - (3) (SI)
Adaptive Control
Prerequisites: EE 621 and EE 724 or permission of instructor
Parametrized control system models, signal norms, Lyapunov stability,
passivity, error models, gradient and least squares algorithms
for parameter estimation, adaptive observers, direct adaptive
control, indirect adaptive control, certainty equivalence principle,
multivariable adaptive control, stability theory of adaptive control,
applications to robot control systems.
EE 827 - (3) (SI)
Multivariable Robust Control Systems
Prerequisites: EE 724 or equivalent or permission of instructor
Advanced topics in modern multivariable control theory. Matrix
fraction descriptions, state-space realizations, multivariable
poles and zeroes; operator norms, singular value analysis. Representation
of unstructured and structured uncertainty, linear fractional
transformation, stability robustness and performance robustness,
parametrization of stabilizing controllers. Approaches to controller
synthesis. H2-optimal control and loop transfer recovery. H-optimal
control and state-space solution methods.
EE 828 - (3) (SI)
Advanced Topics in Control Theory
A seminar course examining current papers from the literature
on recent developments in control. The specific topics to be covered
depend on teacher and student interest.
EE 838/839 - (3) (SI)
Advanced Topics in Digital Systems
Prerequisite: Permission of instructor
A variable content course addressing specific areas of current
interest and importance. Material from the current literature
will be an integral part of any topic covered. Possible topics
include: computer architecture: computer system design, advanced
switching theory, design automation, test technology, fault tolerant
computing, and VLSI.
EE 862 - (3) (SI)
High Speed Transistors
Prerequisite: EE 663 or EE 768 or permission of instructor
Includes the principles of operation, device physics, basic technology,
and modeling of high speed transistors. A brief review of material
properties of most important compound semiconductors and heterostructure
systems, followed by the discussion of high speed Bipolar Junction
Transistor technology, Heterojuction Bipolar Transistors, and
Tunneling Emitter Bipolar Transistors and by the theory and a
comparative study of MESFETs, HFETs, and Variable-Threshold and
Split-gate Field Effect Transistors. Also includes advanced transistor
concepts based on ballistic and hot electron transport in semiconductors
such as Ballistic Injection Transistors and Real Space Transfer
Transistors (RSTs) concepts.
EE 863 - (3) (SI)
High Frequency Diodes
Prerequisites: EE 556, EE 663, or permission of instructor
Lectures on the basic two terminal solid state devices that are
still extensively used in high frequency microwave and millimeter-wave
detector and oscillator circuits. Devices discussed are: PIN Diode
limiters and phase shifters, Schottky Diode mixers and varactors,
Planar-Doped Barrier and Heterostructure Barrier mixer diodes,
Superconducting-Insulating- Superconducting mixer devices, Metal-Semiconductor-Metal
photodetectors, Transferred Electron Devices, IMPATT Diodes, and
Resonant Tunelling Diodes. Basic concepts related to Noise in
high frequency circuits, Mixers, Resonators, and Oscillators are
reviewed. Emphasis on basic device theory, and device fabrication.
EE 868 - (3) (SI)
Special Topics in Semiconductor Materials and Devices
Prerequisite: Permission of instructor
A seminar course with topics chosen from the current literature
according to student interest. Some possible topics include: hot
electron transport effects, degradation mechanisms in semiconductors,
methods of manufacture, applications and limitations of very large
scale integrated circuits (VLSI), device modeling, novel measurement
techniques, submicrometer lithography, and high field breakdown.
EE 881/882 - (3) (SI)
Special Topics in Computer Vision/Imaging Processing
Prerequisite: Permission of instructor
This course is intended for M.S. and Ph.D. students conducting
research in Image Processing Machine Vision. The contents will
vary with each semester and each instructor. An in-depth study
of recent research in a narrowly defined area of computer vision/image
processing will be conducted. Readings from recently published
articles in journals and conference proceedings will be assigned.
Cross-listed as CS 882.
EE 884 - (3) (Y)
Neural Networks
Prerequisite: APMA 615, CS 351, or equivalent
Provides students with a working knowledge of the
fundamental theory, design and applications of artificial neural
networks (ANN). Topics include the major general architectures:
backpropagation, competitive learning, counterpropagation, etc.
Learning rules such as Hebbian, Widrow- Hoff, generalized delta,
Kohonen linear and auto associators, etc., are presented. Specific
architectures such as the Neocognitron, Hopfield-Tank, etc., are
included. Hardware implementation is considered.
EE 886/887 - (3) (SI)
Special Topics in Electrical Engineering
Prerequisite: Permission of instructor
A seminar course with topics chosen from the current literature
according to faculty and student interest. Possible course topics
include developments in field theory, inhomogeneous waveguides,
submillimeter devices, Fourier optics and VLSI design.
EE 895 - (3-6) (S)
Supervised Project Research
Formal record of student commitment to project research
under the guidance of a faculty advisor. Registration may be repeated
as necessary.
EE 897 - (Credit as arranged) (S)
Graduate Teaching Instruction
For Master's students.
EE 898 - (Credit as arranged) (S)
Thesis
Formal record of student commitment to master's thesis
research under the guidance of a faculty advisor. Registration
may be repeated as necessary.
EE 997 - (Credit as arranged) (S)
Graduate Teaching Instruction
For Doctoral students.
EE 999 - (Credit as arranged) (S)
Dissertation
Formal record of student commitment to doctoral research
under the guidance of a faculty advisor. Registration may be repeated
as necessary.
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