Nonlinear System Identification by Haar Wavelets: Lecture Notes in Statistics, cartea 210
Autor Przemysław Sliwinskien Limba Engleză Paperback – 12 oct 2012
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Specificații
ISBN-13: 9783642293955
ISBN-10: 3642293956
Pagini: 150
Ilustrații: XI, 139 p. 27 illus., 18 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.23 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Statistics
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642293956
Pagini: 150
Ilustrații: XI, 139 p. 27 illus., 18 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.23 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Statistics
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Introduction.- Hammerstein systems.- Identification goal.- Haar orthogonal bases.- Identification algorithms.- Computational algorithms. – Final remarks. - Technical derivations.
Recenzii
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)
“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)
Notă biografică
Dr. Przemysław Śliwiński is an assistant professor at the Wrocław 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.
Textul de pe ultima copertă
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.
Caracteristici
Provides nonparametric algorithms based on standard and unbalanced Haar bases Demonstrates applicability of nonlinear approximation schemes to nonlinear system identification Offers fast identification routines Includes supplementary material: sn.pub/extras