Identification of Nonlinear Systems Using Neural Networks and Polynomial Models A Block-Oriented Approach /

• Κύριος συγγραφέας: Janczak, Andrzej (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
• Σειρά: Lecture Notes in Control and Information Science, 310
• Θέματα: Engineering.; System theory.; Statistical physics.; Dynamical systems.; Vibration.; Dynamics.; Control engineering.; Robotics.; Mechatronics.; Control, Robotics, Mechatronics.; Vibration, Dynamical Systems, Control.; Systems Theory, Control.; Statistical Physics, Dynamical Systems and Complexity.

 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. 

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