Identification of Nonlinear Systems Using Neural Networks and Polynomial Models A Block-Oriented Approach /
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 gi...
Κύριος συγγραφέας: | |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2005.
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Σειρά: | Lecture Notes in Control and Information Science,
310 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Περίληψη: | 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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Φυσική περιγραφή: | XIV, 199 p. online resource. |
ISBN: | 9783540315964 |
ISSN: | 0170-8643 ; |