Identification of nonlinear systems using neural networks and polynomial models : a block-oriented approach

書誌事項

Identification of nonlinear systems using neural networks and polynomial models : a block-oriented approach

A. Janczak

(Lecture notes in control and information sciences, 310)

Springer, c2005

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注記

Includes bibliographical references (p. [187]-194) and index

内容説明・目次

内容説明

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.

目次

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

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詳細情報

  • NII書誌ID(NCID)
    BA70065489
  • ISBN
    • 3540231854
  • 出版国コード
    gw
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Berlin
  • ページ数/冊数
    xiv, 197 p.
  • 大きさ
    24 cm
  • 親書誌ID
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