Table of contents

  1. Front Matter
  2. Pages 1-13
  3. Pages 56-88
  4. Pages 89-124
  5. Pages 125-211
  6. Pages 212-213
  7. Back Matter

About this book

Introduction

In deterministic identification the identified system is determined on the basis of a complexity measure of models and a misfit measure of models with respect to data. The choice of these measures and corresponding notions of optimality depend on the objectives of modelling. In this monograph, the cases of exact modelling, model reduction and approximate modelling are investigated. For the case of exact modelling a procedure is presented which is inspired by objectives of simplicity and corroboration. This procedure also gives a new solution for the partial realization problem. Further, appealing measures of complexity and distance for linear systems are defined and explicit numerical expressions are derived. A simple and new procedure for approximating a given system by one of less complexity is described. Finally, procedures and algorithms for deterministic time series analysis are presented. The procedures and algorithms are illustrated by simple examples and by numerical simulations.

Keywords

Regelungstheorie Symbol Time series algorithm algorithms control theory distance dynamical systems dynamische Systeme model modeling signal processing simulation system system theory

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0043065
  • Copyright Information Springer-Verlag 1989
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-51323-0
  • Online ISBN 978-3-540-46196-8
  • Series Print ISSN 0170-8643
  • Series Online ISSN 1610-7411
  • About this book