Nonlinear System Identification by Haar Wavelets

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Springer Science & Business Media, Oct 12, 2012 - Mathematics - 139 pages
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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.
 

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Contents

Chapter 1 Introduction
1
Chapter 2 Hammerstein Systems
5
Chapter 3 Identification Goal
12
Chapter 4 Haar Orthogonal Bases
17
Chapter 5 Identification Algorithms
43
Chapter 6 Computational Algorithms
76
Chapter 7 Final Remarks
95
Appendix A Technical Derivations
99
Appendix B Common Symbols
127
References
129
Index
136
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About the author (2012)

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.

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