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On sampling of continuous time stochastic processes
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-1927-1690
Department of Electrical Engineering, Linköping University.
Uppsala University.
1993 (English)In: Control, theory and advanced technology, ISSN 0911-0704, Vol. 9, no 1, 99-112 p.Article in journal (Refereed) Published
Abstract [en]

Techniques for sampling of continuous time stochastic processes are presented. To obtain flexible models and well-posed filtering problems, we assume an underlying continuous time innovations model. To sample such a model `averaged sampling' is applied. It is shown that this technique is equivalent to the following two step procedure: Determine by instantaneous (direct) sampling a discrete model for the continuous time process obtained by integrating the original innovations model. Then differentiate the sampled process to remove the discrete pole at z = 1 introduced by the integration. An advantage with this procedure is that one obtains ARMA(n, n) models, while instantaneous sampling only gives ARMA(n, n-1) models. Furthermore, the problem of updating discrete time models, without using a continuous time model, in case of a change of sampling rate - decimation/interpolation - is addressed.

Place, publisher, year, edition, pages
1993. Vol. 9, no 1, 99-112 p.
Keyword [en]
Algorithms, Differentiation (calculus), Discrete time control systems, Integration, Interpolation, Mathematical models, Parameter estimation, Sampling, Stochastic control systems, ARMA models, Continuous time systems, Process control
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-55428ISI: A1993LM60600007OAI: diva2:471599

QC 20120104 NR 20140805

Available from: 2012-01-02 Created: 2012-01-02 Last updated: 2016-05-27Bibliographically approved

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