Nonlinear System Identification by Haar Wavelets / Lecture Notes in Statistics Bd.210 (PDF)

Name: Nonlinear System Identification by Haar Wavelets / Lecture Notes in Statistics Bd.210
Brand: Springer-Verlag GmbH
SKU: 43012043
Price: 54.99 EUR
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(Sprache: Englisch)

Autor: Przemyslaw Sliwinski

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Nonlinear System Identification by Haar Wavelets / Lecture Notes in Statistics Bd.210, Przemyslaw Sliwinski

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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.

Autoren-Porträt von Przemyslaw Sliwinski

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.

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Autor: Przemyslaw Sliwinski
2012, 2013, 139 Seiten, Englisch
Verlag: Springer-Verlag GmbH
ISBN-10: 3642293964
ISBN-13: 9783642293962
Erscheinungsdatum: 12.10.2012

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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)

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