Identification of nonlinear systems using neural networks and polynomial models : a block-oriented approach / A. Janczak.
"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 b...
Saved in:
| Main Author: | |
|---|---|
| Corporate Author: | |
| Format: | Ebook |
| Language: | English |
| Published: |
Berlin ; New York :
Springer,
c2005.
|
| Series: | Lecture notes in control and information sciences ;
310. |
| Subjects: | |
| Online Access: | Springer eBooks |
| Summary: | "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."--Publisher's website. |
|---|---|
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references (p. [187]-194) and index. |
| ISBN: | 1281390186 3540315969 9781281390189 9783540315964 |