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Identification of Nonlinear Systems Using Neural Networks and Polynomial Models: A Block-Oriented Approach
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(Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!
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| 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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Auf Bestellung (Lieferzeit unbekannt)
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