On Sampling of Continuous Time Stochastic Processes
1993 (English)In: Control, Theory and Advanced Technology, ISSN 0911-0704, Vol. 9, no 1, 99-112 p.Article in journal (Refereed) Published
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.
Algorithms, Differentiation (calculus), Discrete time control systems, Integration, Interpolation, Mathematical models, Parameter estimation, Sampling, Stochastic control systems, ARMA models, Continuous time systems, Process control
IdentifiersURN: urn:nbn:se:liu:diva-95655OAI: oai:DiVA.org:liu-95655DiVA: diva2:637117