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.

List of contents

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

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.

Product details

• Authors: Andrzej Janczak
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 29.11.2004
• EAN: 9783540231851
• ISBN: 978-3-540-23185-1
• No. of pages: 199
• Weight: 344 g
• Illustrations: XIV, 199 p.
• Series: Lecture Notes in Control and Information Sciences; Lecture Notes in Control and Information Sciences
• Subjects: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering; 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