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 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.

Sommario

Introduction.- Neural network Wiener models.- Neural network Hammerstein models.- Polynomial Wiener models.- Polynomial Hammerstein models.- Applications.

Riassunto

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.

Dettagli sul prodotto

• Autori: Andrzej Janczak
• Editore: Springer, Berlin
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 29.11.2004
• EAN: 9783540231851
• ISBN: 978-3-540-23185-1
• Pagine: 199
• Peso: 344 g
• Illustrazioni: XIV, 199 p.
• Serie: Lecture Notes in Control and Information Sciences; Lecture Notes in Control and Information Sciences
• Categorie: Scienze naturali, medicina, informatica, tecnica > Tecnica > Elettronica, elettrotecnica, telecomunicazioni; B, Robotics, Vibration, engineering, Civil Engineering, Dynamics, Complex systems, Theoretical, Mathematical and Computational Physics, Systems Theory, Control, Electronic devices & materials, Mechanics of solids, Dynamical systems, Control, Robotics, Mechatronics, Control, Robotics, Automation, Control engineering, Mechatronics, System Theory, Cybernetics & systems theory, Dynamics & statics, Statistical physics, Vibration, Dynamical Systems, Control, Statistical Physics and Dynamical Systems