Nonlinear System Identification by Haar Wavelets (eBook)

Przemysław Sliwinski (Autor)

eBook Download: PDF

2012 | 2013
XI, 139 Seiten
Springer Berlin (Verlag)
978-3-642-29396-2 (ISBN)

Infos

?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. ? ?

Dr. Przemys?aw ?liwi?ski is an assistant professor at the Wroc?aw 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.

Autor

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.

Inhalt

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

Produkt-Details

• Erscheint lt. Verlag: 12.10.2012
• Reihe/Serie: Lecture Notes in Statistics
• Reihe/Serie: Lecture Notes in Statistics
• Zusatzinfo: XI, 139 p. 27 illus., 18 illus. in color.
• Verlagsort: Berlin
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Technik
• Schlagworte: Computational Algorithms • Haar bases • nonlinear approximation • nonlinear system identification • nonparametric algorithms • regression estimation
• ISBN-10: 3-642-29396-4 / 3642293964
• ISBN-13: 978-3-642-29396-2 / 9783642293962