Nonlinear System Identification by Haar Wavelets

  • Przemysław Śliwiński

Part of the Lecture Notes in Statistics book series (LNS, volume 210)

Table of contents

  1. Front Matter
    Pages i-xi
  2. Przemysław Śliwiński
    Pages 1-4
  3. Przemysław Śliwiński
    Pages 5-11
  4. Przemysław Śliwiński
    Pages 13-16
  5. Przemysław Śliwiński
    Pages 17-41
  6. Przemysław Śliwiński
    Pages 43-75
  7. Przemysław Śliwiński
    Pages 77-93
  8. Przemysław Śliwiński
    Pages 95-98
  9. Back Matter
    Pages 99-139

About this book

Introduction

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.

Keywords

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

Authors and affiliations

  • Przemysław Śliwiński
    • 1
  1. 1.Institute of Computer Engineering,, Control and RoboticsWrocław University of TechnologyWrocławPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-29396-2
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-642-29395-5
  • Online ISBN 978-3-642-29396-2
  • Series Print ISSN 0930-0325
  • About this book