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

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Item description for Identification of Nonlinear Systems Using Neural Networks and Polynomial Models: A Block-Oriented Approach (Lecture Notes in Control and Information Sciences) by A. Janczak...

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.





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Item Specifications...


Pages   199
Est. Packaging Dimensions:   Length: 9.21" Width: 5.91" Height: 0.55"
Weight:   0.62 lbs.
Binding  Softcover
Release Date   Dec 22, 2004
Publisher   Springer
ISBN  3540231854  
ISBN13  9783540231851  


Availability  53 units.
Availability accurate as of Mar 28, 2017 07:36.
Usually ships within one to two business days from La Vergne, TN.
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