Sliwinski Nonlinear System Identification by Haar Wavelets

1. Auflage 2012
ISBN: 978-3-642-29396-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 210, 139 Seiten, eBook

Reihe: Lecture Notes in Statistics

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.

Zielgruppe

Research

Autoren/Hrsg.

Sliwinski, Przemyslaw

Inhaltsverzeichnis

Introduction.- Hammerstein systems.- Identification goal.- Haar orthogonal bases.- Identification algorithms.- Computational algorithms. – Final remarks. - Technical derivations.

Über Autor(innen)

Dr. Przemyslaw Sliwinski is an assistant professor at the Wroclaw University of Technology, where he received his master’s degree in 1996 and his PhD in 2000. For his master’s degree he developed an integrated development environment with a software emulator of a micro-controller. His PhD dissertation addressed the problems of nonlinear system identification using linear wavelet estimation algorithms.