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Statistics - Statistical Theory and Methods | Nonlinear System Identification by Haar Wavelets

Nonlinear System Identification by Haar Wavelets

Series: Lecture Notes in Statistics, Vol. 210

Sliwinski, Przemysław

2013, XI, 139 p. 27 illus., 18 illus. in color.

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  • Provides nonparametric algorithms based on standard and unbalanced Haar bases
  • Demonstrates applicability of nonlinear approximation schemes to nonlinear system identification
  • Offers fast identification routines

In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener series is capable of representing fairly complicated nonlinear and dynamic interactions, however, the resulting identification algorithms are impractical, mainly due to their computational complexity. One of the alternatives offering fast identification algorithms is the block-oriented approach, in which systems of relatively simple structures are considered. The book provides nonparametric identification algorithms designed for such systems together with the description of their asymptotic and computational properties.

Content Level » Research

Keywords » Haar bases - computational algorithms - nonlinear approximation - nonlinear system identification - nonparametric algorithms - regression estimation

Related subjects » Statistical Theory and Methods

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