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On Sampling of Continuous Time Stochastic Processes
Royal Institute of Technology, Sweden.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Uppsala University, Sweden.
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:liu:diva-95655OAI: diva2:637117
Available from: 2013-07-16 Created: 2013-07-16 Last updated: 2013-07-16

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