Neural Network Engineering in Dynamic Control Systems
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Author
Contributions
- Irwin, George R. - Contributor
- Warwick, Kevin - Contributor
Publication
1995 - Springer London, London, United Kingdom
Language
English
Word Count
70,500 words, Guess
Page Count
282 pages
Physical Format
Electronic resource
Identifiers
- Internet Archiveneuralnetworkeng00biko
- ISBN-101447130685
- ISBN-101447130669
- ISBN-139781447130680
- ISBN-139781447130666
and 3 more
- OCLC Control Number853256828
- Better World Books9781447130680
- Open LibraryOL27076993M
Classifications
- DDC629.8
- LCCTJ212-225
Description
This study evaluates the state of the art in the area of neural networks from the engineering perspective. The contributions examine ways of improving the engineering involved in neural network modelling and control, so that the theoretical power of learning systems can be harnessed for practical applications. Neural Network Engineering in Dynamic Control Systems seeks to provide answers to the following questions: * Which network architecture for which application? * Can constructive learning algorithms capture the underlying dynamics while avoiding overfitting? * How can we introduce a priori knowledge or models into neural networks? * Can experimental design and active learning be used automatically to create "optimal" training sets? * How can we validate a neural network model?
Subjects
Series Statement
- Advances in Industrial Control
Other Editions
- Neural Network Engineering in Dynamic Control Systems
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