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   -> Volume 6, Issue 3


Course: Wavelets, Fuzzy Logic, Chaos, and Neural Networks
 
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"Goodin, Bill" (bgoodin@unex.ucla.edu)
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PostPosted: Wed Mar 05, 1997 5:39 pm    
Subject: Course: Wavelets, Fuzzy Logic, Chaos, and Neural Networks
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#13 Course: Wavelets, Fuzzy Logic, Chaos, and Neural Networks

On June 2-6, 1997, UCLA Extension will present the short course,
"Wavelets, Fuzzy Logic, Chaos, and Neural Networks: Multiresolution
Soft-Computing Principles and Applications", on the UCLA campus in Los
Angeles.

The instructor is Harold Szu, PhD, Lamson Professor of Computer
Science, University of Southwestern Louisiana, Lafayette, and Past
President of the International Neural Network Society (INNS).

This course presents the multiresolution soft-computing principles and
applications of several different but related disciplines--wavelets,
neural networks, fuzzy logic, and chaos--in the context of
multiresolution granularity in human sensors system. This
"soft-computing" with words instead of yes-or-no binary logic is
useful for signal classification and compression, pattern recognition,
control of engineering tolerance imprecision, and the prediction of
fluctuating time series.

Various applications in chaos, fuzzy logic, wavelet transforms and
neural net learning are illustrated in terms of spatiotemporal
information processing, such as: signal/image de-noise; signal
classification; control device/machine chaos; communication coding;
chaotic heart and biomedical applications; intelligent bisensors such
as pacemakers and hearing aids; bomb 'sniffers'; and discrete wavelet
transform subband coding for image compression.

The course fee is $1495, which includes extensive course materials.
These materials are for participants only, and are not for sale.

For additional information and a complete course description, please
contact Marcus Hennessy at:

(310) 825-1047
(310) 206-2815 fax
mhenness@unex.ucla.edu
http://www.unex.ucla.edu/shortcourses

This course may also be presented on-site at company locations.
All times are GMT + 1 Hour
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