£89.20

Springer Identification of Nonlinear Systems Using Neural Networks and Polynomial Models: A Block-Oriented Approach: 310 (Lecture Notes in Control and Information Sciences, 310)

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Description

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 Specifications

Format
paperback
Domain
Amazon UK
Release Date
18 November 2004
Listed Since
27 December 2006

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