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Presenter
Professor John Mathews (University of Utah)
V. John Mathews is Professor and Chairman of the Department of
Electrical and Computer Engineering at the University of Utah.
He received the PhD degree from the University of Iowa in 1984
and has been at Utah ever since. His research and teaching interests
are in adaptive and nonlinear
filters and their applications. He co-authored the book Polynomial
Signal Processing (Wiley, 2000) with G. L. Sicuranza. He has served
as the associate editor for IEEE Transactions on Signal Processing
and IEEE Signal Processing Letters, as the General Chairman for
IEEE International
Conference on Acoustics, Speech and Signal Processing, 2001, and
as a member of the IEEE Signal Processing Society’s Signal
Processing Theory and Methods and Education Technical Committees.
He is a Fellow of the IEEE.
Dates
July 22nd and 23rd, 2002
Course Content
This two-day course is designed for students with a basic background
in digital signal processing techniques. The underlying principles
of a variety of adaptive algorithms will be discussed. The development
of least mean-square (LMS) adaptive filters and their variations
for FIR, IIR and nonlinear system models will be presented. Associated
topics covered include: Performance evaluation of adaptive algorithms
using simple analysis and experiments, Design rules for choice
of parameters, Extensions to lattice structures, frequency domain
implementations, and recursive least-squares algorithms. The presentations
will be mixed with applications and MATLAB exercises throughout
the duration of the course. Students will also be provided with
information on current literature for further exploration.
Outline:
July 22
Morning
Introduction and LMS Adaptive Filters
Need for adaptive filters and basic problem formulation.
Stochastic gradient adaptive filters for different cost functions.
Derivation of least-mean-square (LMS) adaptive filter for FIR,
IIR, nonlinear, and cascade system models.
Afternoon
Performance Evaluation and Extensions
A simple convergence analysis of FIR LMS adaptive filters.
Design rules for choosing the parameters. Algorithms for adapting
the parameters online.
Derivation of the recursive least-squares (RLS) adaptive filter
as an extension of the LMS adaptive filter.
Stability of adaptive IIR filters.
July 23
Morning
Transform-Domain Realizations of LMS Adaptive Filters
Review of discrete Fourier transform (DFT), discrete cosine
transform (DCT) and filter banks for signal analysis.
Derivation of adaptive filters operating in the transform domain.
Performance evaluation and comparisons.
Afternoon
Adaptive Lattice Filters
Gram-Schmidt orthogonalization and the lattice structure for
FIR filters.
Adaptation of the parameters of the lattice structure.
Comparisons with direct form algorithms.
Concluding discussion, course review
Who should attend
This is a course designed for practising engineers and scientists
in academia and industry as well as graduate students working
on signal processing problems. The course will assume a basic
knowledge of digital signal processing algorithms involving linear
system analysis, design and realisation, and signal analysis in
the time and frequency domain. Some matrix algebra and an introductory
understanding of random processes are desirable.
Venue: This course will be held at the Signal Processing
Research Institute, Mawson Lakes Boulevard, Mawson Lakes, South
Australia.
Registration Fee and Enquiries
Fee for 2 day course $1000 Plus GST
Employees and students of CSSIP partners $800 Plus GST
Sponsored places may be available to CSSIP researchers and students
under the usual arrangements. Please enquire.
Please complete the enclosed registration form and send it together
with your fee, if appropriate, to the address on the form, by
no later than 8 July 2002.
For general enquiries about this and other short courses contact:
Anne-Marie Eliseo
Education Manager
SPRI Building
Mawson Lakes Boulevard
MAWSON LAKES
South Australia 5095
Phone: +61 8 8302 3928
Fax: +61 8 8302 3124
Email: education@cssip.edu.au
All enquiries about postgraduate credit possibilities should
in the first instance be addressed to the CSSIP Continuing Education
Manager (see above).
Register Interest : education@cssip.edu.au
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