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- Newsgroups: comp.parallel
- Path: sparky!uunet!digex.com!intercon!udel!gatech!hubcap!sdcc12!xm8
- From: xm8@sdcc12.ucsd.edu (patrick k. simpson)
- Subject: Neural/Fuzzy Applications Course
- Message-ID: <1993Jan27.174042.2192@hubcap.clemson.edu>
- To: comp-parallel@sdcc12.UCSD.EDU
- Followup-To: poster
- Keywords: Neural Networks, Fuzzy Systems, Course Announcement
- Sender: news@sdcc12.ucsd.edu
- Nntp-Posting-Host: sdcc12.ucsd.edu
- Organization: Clemson University
- Date: 27 Jan 93 16:56:17 GMT
- Approved: parallel@hubcap.clemson.edu
- Lines: 152
-
-
-
- COURSE ANNOUNCMENT
-
- APPLICATIONS OF NEURAL NETWORKS AND FUZZY SYSTEMS
-
- Date:
- April 13-15, 1993
- 8:30 am - 4:00 pm
-
- Location:
- Catamaran Resort Hotel
- 3999 Mission Blvd.
- San Diego, CA
- Ph. 619/488-1081
-
- Registration:
- Tuition $990.00
- Applied Technology Institute
- 12960 Linden Church Road
- P.O. Box 1172
- Clarksville, MD 21029
- Phone (410) 531-6034
- Fax (410) 531-1013
-
- Summary:
-
- Applications of Neural Networks and Fuzzy Systems will immerse the
- student in the most recent results in neural networks and fuzzy systems
- to applications in some of the most difficult problems in computing today.
- Application areas will be explored in detail, including sonar, radar,
- communications, signal processing, diagnostics, sensor and data fusion,
- forecasting, prediction, modelling, and control. The applications include
- an extensive description of the work conducted in both Europe and Japan,
- as well as a full spectrum of the state-of-the-art in these rapidly growing
- fields.
-
- "Applications of Neural Networks and Fuzzy Systems" serves those
- individuals who want to know what neural networks and fuzzy systems are
- and how they can be applied. This course distributes information
- that explains what products and services are currently available accompanied
- by the instructors recommendations and experience. Each course distributes a
- book that provides a broad overview of neural networks and their applications,
- survey papers that provide descibe specific applications areas, and
- demonstation software (including source code). In-class demonstrations place
- the student as close to real-world applications as possible without actually
- going into the laboratory.
-
- The text, "Artificial Neural Systems: Foundations, Paradigms,
- Applications and Implementations," written by the instructor, will be
- provided to all students.
-
- Instructor:
-
- Patrick K. Simpson is a Principal Engineer at ORINCON Corporation, a
- small-business dedicated to the application of intelligent systems to
- difficult defense-related problems. Mr. Simpson is an active member of
- the IEEE, having served on the organization committees of several
- international neural network and fuzzy system conferences as well
- as holding several executive positions on the IEEE Neural Networks
- Council. Mr. Simpson was the Program Chairman of the first IEEE Conference
- on Neural Networks for Ocean Engineering, a lecturer for the NATO Lecture
- Series dedicated to the application of neural networks to guidance and
- control and a member of Who's Who in Science and Engineering. Mr. Simpson
- has written several papers on theory and application of neural networks
- and fuzzy systems as well as the book "Artificial Neural Systems: Foundations,
- Paradigms, Applications and Implementations."
-
- COURSE OUTLINE:
-
- Applications of Neural Networks and Fuzzy Systems is broken into
- three parts that span three intensive, but enjoyable, days. Neural networks
- and fuzzy systems are first individually described. In the third part, hybrid
- fuzzy neural systems are described and applications are presented.
-
- Part One: Neural Networks.
-
- * A broad overview of neural networks. What are neural networks:
- Why are they so appealing: What can they do? What can't they do?
-
- * Neural Network Paradigms. The fundamental components and
- nomenclature.
-
- * Neural Network Design Methodology. A sequence of design steps is
- developed that will allow an engineer or scientist to easily apply
- neural networks.
-
- * Neural Network Complexity Analysis. Trade-Offs are examined, such
- as: size vs. speed, training time vs. run-time, and generalization
- vs. memorization.
-
- * Sonar Applications. Application areas include: beamforming,
- noise cancellation, feature extraction, detection, and classification.
-
- * Communication Applications. Application areas include: adaptive
- equalization, network control, data compression, error correction, and
- multi-user detection.
-
- * Radar Applications. Applications include clutter rejection, signal
- classification, deinterleaving, and emmitter identification.
-
- * Diagnostic Applications. Historical diagnostic vs. model-based
- diagnostics.
-
- * Forecasting, Prediction, and Modelling. Applications and
- techniques will include chaotic time-series prediction,
- forecasting environmental phenomena, and financial market prediction
- (stocks, commodities, etc.).
-
- * Sensor and Data Fusion. Different methods of fusion. Applications to
- surveillance, control, and diagnotistics.
-
- * Software and Hardware Review. A review of the currently available
- software and hardware that includes manufacturer's demo disks and
- ordering information. A complete listing of shareware software
- will be provided.
-
- Part Two: Fuzzy Systems.
-
- * Introduction to Fuzzy Systems. Answers to some fundamental
- questions, like: What is a fuzzy system: How is fuzzy different
- from probabilistic? Why use a fuzzy system?
-
- * Fuzzy Control Systems. Applications will be described, including:
- auto-focusing cameras and aircraft control.
-
- * Fuzzy Expert Systems. Applications to commercial appliances, data
- fusion, and decision aides.
-
- * Software and Hardware Review. A review of currently available
- software and hardware that includes manufacturer's demo disks and
- ordering information.
-
- Part Three: Fuzzy Neural Systems.
-
- * Methods of synergistically combining neural networks and fuzzy
- systems. Neural networks and fuzzy systems can be effectively combined
- to provide a more competent system.
-
- * Fuzzy Neural Control. Several exmples are provided that demonstrate a
- natural bridge between the two technologies.
-
- * Fuzzy Neural Pattern Clustering and Classification. The state-of-the-art
- in pattern recognition lies in the synergism of these two technologies. A
- detailed description of several approaches will be provided.
-
-
- For Immediate Registration Phone (410) 531-6034 or Mail Check or
- Purchase Order to Applied Technology Institute, 12960 Linden Church Road,
- P.O. Box 1172, Clarksville, MD 21029 Fax (410) 531-1013
-
-
-