Identification of Nonlinear Systems Using Neural Networks and Polynomial Models : A Block-Oriented Approach
Language: English
Published by Springer Vieweg, Springer, 2004
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Seller Inventory # 9783540231851
- Title
- Identification of Nonlinear Systems Using Neural Networks and Polynomial Models : A Block-Oriented Approach
- Author
- Andrzej Janczak
- Publisher
- Springer Vieweg, Springer
- Publication year
- 2004
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3540231854
- ISBN 13
- 9783540231851
- Item weight
- 341 grams
- Dimensions
- 235x155x13 mm
This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the identification of Wiener and Hammerstein systems which are applicable to both neural network and polynomial models. The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models" is useful for researchers, engineers and graduate students in nonlinear systems and neural network theory.
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