Nonlinear System Identification by Haar Wavelets

1. Front Matter

   Pages i-xi

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2. Introduction

   • Przemysław Śliwiński

   Pages 1-4

3. Hammerstein Systems

   • Przemysław Śliwiński

   Pages 5-11

4. Identification Goal

   • Przemysław Śliwiński

   Pages 13-16

5. Haar Orthogonal Bases

   • Przemysław Śliwiński

   Pages 17-41

6. Identification Algorithms

   • Przemysław Śliwiński

   Pages 43-75

7. Computational Algorithms

   • Przemysław Śliwiński

   Pages 77-93

8. Final Remarks

   • Przemysław Śliwiński

   Pages 95-98

9. Back Matter

   Pages 99-139

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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. ​ ​

• Haar bases
• computational algorithms
• nonlinear approximation
• nonlinear system identification
• nonparametric algorithms
• regression estimation

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)

• Institute of Computer Engineering,, Control and Robotics, Wrocław University of Technology, Wrocław, Poland

  Przemysław Śliwiński

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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