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High-accuracy instrumental variable identification of continuous-time autoregressive parameters from irregularly sampled noisy data
Karlstad University, Faculty of Technology and Science, Department of Physics and Electrical Engineering.
2008 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 56, no 8, p. 4087-4091Article in journal (Refereed) Published
Abstract [en]

A computationally efficient estimator of continuous-time autoregressive (AR) process parameters from irregularly sampled data affected by discrete-time white measurement noise is presented. It is described how an instrumental variable approach can be used for estimating the AR process parameters with high accuracy. Possible estimators of the incremental variance of the driving continuous-time white noise source and of the variance of the discrete-time white measurement noise are also discussed.

Place, publisher, year, edition, pages
2008. Vol. 56, no 8, p. 4087-4091
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Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
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URN: urn:nbn:se:kau:diva-19978DOI: 10.1109/TSP.2008.925578OAI: oai:DiVA.org:kau-19978DiVA, id: diva2:593633
Available from: 2013-01-21 Created: 2013-01-21 Last updated: 2017-12-06Bibliographically approved

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Mossberg, Magnus

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