System Identification - General Aspects and Structure

  • Manfred Deistler

Abstract

System identification is concerned with finding a good model from, in general, noisy data, i.e. with data driven modeling. Often the task of identification is so complex that it cannot be performed in a naive way with the naked eye. In addition many identification problems share common features. For these reasons methods and theories have been developed which make system identification a subject of its own. This is the case despite the fact that problems of system identification are treated in different and partly rather separated communities, such as in system and control theory, signal processing, statistics and econometrics; the latter is explained by the fact that system identification is a central issue in many branches of science and has a wide range of areas of applications from control of chemical processes to the analysis of earth quake data or forecasting of sales for firms. Accordingly, we will use the term system identification for data driven modeling in general, i.e. not necessarily relating to system and control theory

Keywords

Manifold Covariance Eter Volatility Librium 

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Copyright information

© Springer-Verlag London Limited 2001

Authors and Affiliations

  • Manfred Deistler
    • 1
  1. 1.Institut für ÖkonometrieOperations Research und Systemtheorie Technische Universität WienWienAustralia

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