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ATI's Neural and Evolutionary Computation course
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Summary:
There have been tremendous advances in the technologies of artificial neural networks and
evolutionary computation for addressing difficult problems. These technologies have been
successfully applied to signal and image processing, logistics, tactics optimization, fire
control, data compression, antenna design, and other problems. Many potential users of
these technologies are hindered by the absence of a suitable overview giving an integrated
development that links neural and evolutionary computation for synergistic effects. The
objectives of this three-day course are a) to give a practical introduction to the use of
neural and evolutionary computation in real-world problems, b) indicate when these techniques may be most appropriately applied, c) to provide a framework that enables the student to be able to put the essential elements of these techniques into practice.
The book Evolutionary Computation: The Fossil Record, edited by Dr. David B. Fogel,
and a complete set of course notes will be given to each participant. The book is the result
of four years of work documenting the development and current state of the art in evolutionary
computation. Introductory computer programs illustrating some of the basic
procedures will also be distributed.
Instructors:
Dr. David B. Fogel is Executive Vice President and Chief Scientist of Natural
Selection, Inc. He has a Ph.D. in Engineering Sciences from the University of California
at San Diego. Dr. Fogel has 14 years of experience in applying evolutionary algorithms to
complex real-world problems in industry, medicine, and defense. He is the author of over 125
papers in journal and conferences, the author and editor of two books on evolutionary
computation "Evolutionary Computation: Toward a New Philosophy of Machine
Intelligence," and "Evolutionary Computation: The Fossil Record," He is the founding
Editor-in-Chief of the IEEE Transactions on Evolutionary Computation. Dr. Fogel also
served as associate editor for the IEEE Transactions on Neural Networks, and is on the
editorial boards of Fuzzy Sets & Systems, Information Sciences, and the Journal of
Advanced Computational Intelligence.
Mr. Bill Porto is Vice President of Natural Selection, Inc. He has over 15 years
of experience with neural and evolutionary computation, with an particular emphasis in
defense-related applications. Mr. Porto is an Associate Editor for the IEEE Transactions
on Evolutionary Computation, and was the General Chairman of the 7th Annual Conference
on Evolutionary Programming. He has been a member of ONR Panel on Neural Networks and
the organizing committees for the 1988 and 1989 International Joint Conferences on
Neural Networks. Mr. Porto has numerous publications in conferences and journals.
Dr. Peter J. Angeline is Senior Staff Scientist of Natural Selection, Inc.
Dr. Angeline holds a Ph.D. in Computer and Information Sciences from the Ohio
State University. He has 10 years of experience applying neural and
evolutionary algorithms to problems in image processing and combinatorial
optimization. Dr. Angeline is an editor of two books ("Advances in Genetic
Programming II" and "Advances in Genetic Programming III" from MIT Press). He
serves as an Associate Editor for the IEEE Transactions on Evolutionary
Computation. He has served as an Associate Editor for the IEEE Transactions
on Neural Networks, and was a board member of the International Society for
Genetic Algorithms and is Past-President of the Evolutionary Programming
Society. He was also the General Chairman for the 1999 Congress on
Evolutionary Computation.
Contact these instructors (please mention course name in the subject line)
What you will learn:
- Fundamental concepts in neural networks and evolutionary computation.
- How to compare and identify the most appropriate neural and evolutionary algorithms.
- How to implement neural networks and evolutionary algorithms for your own problems.
- How to optimize performance.
- Lessons learned and pitfalls to avoid.
- Emerging trends in applications.
Course Outline:
- Foundations of Artificial Neural Systems. A review of the basics of neural
processing elements, threshold functions, different topologies, memory, learning, stability,
and the convergence of neural systems.
- Alternative Implementations of Neural Networks. A historical perspective and
description of neural architectures for data processing including multilayer perceptrons,
Adaline/Madaline, competitive learning, recurrent connections, cascade-correlation, radial
basis functions.
- Applications of Neural Networks. An overview of applications of neural networks
with particular emphasis on problems in signal and image processing, pattern classification,
forecasting, and control.
- Foundations of Evolutionary Computation. Fundamentals of evolutionary algorithms
including the use of a population of contending solutions, random variation, and selection
iterated over successive generations.
- Alternative Implementations of Evolutionary Computation. A historical perspective
and description of evolutionary algorithms including genetic algorithms, evolutionary
programming, genetic programming, classifier systems, evolution strategies, and artificial life.
- Applications of Evolutionary Computation. An overview of applications of
evolutionary computation in problems in signal and image processing, pattern classification,
forecasting, and control.
- Hybrid Methods of Neural and Evolutionary Computation. How evolutionary computation
can be used to assist in the training and design of neural networks at multiple levels
including weights, connections, and the number and types of neurons.
- Alternative optimization methods. Which procedures are appropriate for your problems
of interest. Classic methods compared with neural and evolutionary computation.
- Case Studies of Neural and Evolutionary Computation. In-depth treatment of
applications to real-world problems with emphasis in signal processing, image analysis, fire
control, and the design of intelligently interactive computer-generated forces.
- Emerging Technology and Future Trends.
Tuition:
Tuition for this three-day course is $1290 per person at one of our scheduled public courses. Onsite pricing is available. Please call us at 410-956-8805 or send an email to ati@aticourses.com.
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