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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...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2005.
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| Edición: | 1st ed. 2005. |
| Colección: | Lecture Notes in Control and Information Sciences,
310 |
| Temas: | |
| Acceso en línea: | Texto Completo |
| Sumario: | 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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| Descripción Física: | XIV, 199 p. online resource. |
| ISBN: | 9783540315964 |
| ISSN: | 1610-7411 ; |