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.
Produkteigenschaften
- Artikelnummer: 9783540231851
- Medium: Buch
- ISBN: 978-3-540-23185-1
- Verlag: Springer Berlin Heidelberg
- Erscheinungstermin: 18.11.2004
- Sprache(n): Englisch
- Auflage: 2005
- Serie: Lecture Notes in Control and Information Sciences
- Produktform: Kartoniert
- Gewicht: 341 g
- Seiten: 199
- Format (B x H x T): 155 x 235 x 13 mm
- Ausgabetyp: Kein, Unbekannt
Themen
- Technische Wissenschaften
- Maschinenbau | Werkstoffkunde
- Technische Mechanik | Werkstoffkunde
- Statik, Dynamik, Kinetik, Kinematik
- Technische Wissenschaften
- Maschinenbau | Werkstoffkunde
- Technische Mechanik | Werkstoffkunde
- Statik, Dynamik, Kinetik, Kinematik