Duke University 2008-2009 - Office of the Registrar - Duke University

288. Sensor Array Signal Processing. An in-depth treatment of the fundamental concepts,
theory, and practice of sensor array processing of signals carried by propagating waves.
Topics include: multidimensional frequency-domain representations of space-time signals
and linear systems; apertures and sampling of space-time signals; beamforming and filtering
in the space-time and frequency domains, discrete random fields; adaptive beamforming
methods; high resolution spatial spectral estimation; optimal detection, estimation, and
performance bounds for sensor arrays; wave propagation models used in sensor array
processing; blind beamforming and source separation methods; multiple-input-multipleoutput
(MIMO) array processing; application examples from radar, sonar, and communications
systems. Instructor: Staff. 3 units.
289. Adaptive Filters. Adaptive digital signal processing with emphasis on the theory and
design of finite-impulse response adaptive filters. Stationary discrete-time stochastic
processes, Wiener filter theory, the method of steepest descent, adaptive transverse filters
using gradient-vector estimation, analysis of the LMS algorithm, least-squares methods,
recursive least squares and least squares lattic adaptive filters. Application examples in noise
canceling, channel equalization, and array processing. Prerequisites: Electrical and
Computer Engineering 281 and 282 or consent of instructor. Instructor: Krolik. 3 units.
298. Advanced Topics in Electrical and Computer Engineering. Opportunity for study
of advanced subjects in electrical and computer engineering. Instructor: Staff. 1 unit.
299. Advanced Topics in Electrical and Computer Engineering. Opportunity for study
of advanced subjects related to programs within the electrical and computer engineering
department tailored to fit the requirements of a small group. Instructor: Staff. 3 units.
For Graduate Students Only
310. Foundations of Nanoscale Science and Technology. This course is the introductory
course for the Graduate Certificate Program in Nanoscience (GPNANO) and is designed to
introduce students to the interdisciplinary aspects of nanoscience by integrating important
components of the broad research field together. This integrated approach will cross the
traditional disciplines of biology, chemistry, electrical & computer engineering, computer
science, and physics. Fundamental properties of materials at the nanoscale, synthesis of
nanoparticles, characterization tools, and self-assembly. Prerequisites: Physics 62L and
Chem 21L or instructor approval. C-L: NANO 200 pending in COMPSCI, CHEM, and
PHYS. Instructor: Dwyer. 3 units. C-L: Nanosciences 310
316. Advanced Physics of Semiconductor Devices. Semiconductor materials: band
structure and carrier statistics. Advanced treatments of metal-semiconductor contacts,
Schottky barriers, p-n junctions, bipolar transistors (charge-control and Gummel-Poon
models), and field-effect transistors (short channel effects, scaling theory, subthreshold
conduction, nonuniformly doped substrates, surface and buried-channel devices, hotelectron
effects). Device modeling in two dimensions using PISCES. Prerequisite: Electrical
Engineering 216. Instructor: Massoud. 3 units.
318. Integrated Circuit Fabrication Laboratory. Introduction to IC fabrication processes.
Device layout. Mask design and technology. Wafer cleaning, etching, thermal oxidation,
thermal diffusion, lithography, and metallization. Laboratory fabrication and characterization
of basic IC elements (p-n junctions, resistors, MOS capacitors, gated diodes, and
MOSFETs). Use of four-point probe, ellipsometer, spreading resistance probe, scanning
electron microscope, and evaporation system. Testing of basic inverters and gates.
Prerequisite: Electrical Engineering 218 and consent of instructor. Instructor: Massoud. 3
units.
352. Advanced Topics in Digital Systems. A selection of advanced topics from the areas
of digital computer architectures and fault-tolerant computer design. Prerequisite: Electrical
Engineering 252 or equivalent. Instructor: Staff. 3 units. C-L: Computer Science 320
361. Advanced VLSI Design. 3 units. C-L: see Computer Science 322
Courses of Instruction 153