Nonlinear System Identification by Haar Wavelets
1st Edition
Published on 12. October 2012
XI, 139 pages
978-3-642-29396-2 (ISBN)
Description
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.
Reviews / Votes
From the book reviews:
"This book is focused on identification algorithms, in particular, nonparametric identification algorithms for nonlinear dynamic systems. . This book can be a good reference for people interested in the application of wavelets in a nonlinear system. The writing style of the book makes it easy to read." (Don Hong, Mathematical Reviews, July, 2014)More details
Series
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XI, 139 p. 27 illus., 18 illus. in color.
File size
2,72 MB
ISBN-13
978-3-642-29396-2 (9783642293962)
DOI
10.1007/978-3-642-29396-2
Schweitzer Classification
Other editions
Additional editions
Przemyslaw Sliwinski
Nonlinear System Identification by Haar Wavelets
Book
10/2012
Springer
€53.49
Shipment within 7-9 days
Person
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.
Content
Introduction.- Hammerstein systems.- Identification goal.- Haar orthogonal bases.- Identification algorithms.- Computational algorithms. - Final remarks. - Technical derivations.
