Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/14087
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dc.contributor.authorAllahyani, S-
dc.contributor.authorDate, P-
dc.coverage.spatialBudapest-
dc.date.accessioned2017-02-22T12:13:40Z-
dc.date.available2016-12-01-
dc.date.available2017-02-22T12:13:40Z-
dc.date.issued2016-
dc.identifier.citation24th European Signal Processing Conference (EUSIPCO), Budapest, Hungary, 29 August - 2 September, (2016)en_US
dc.identifier.issn2219-5491-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/14087-
dc.description.abstractIn this paper, we extend the minimum variance filter, which is proposed in the literature for discrete state space systems with multiplicative noise, to continuous-discrete systems with multiplicative noise. The differential equations that describe the process are discretised using the Euler scheme at a higher sampling frequency than the measurement frequency. We test the performance of our new filter i.e. continuous discrete filter (CDF) on simulated numerical examples and compare the results with discrete discrete filter (DDF) which ignores the state behaviour in-between the measurement samples. The results show that the CDF outperforms the DDF in all the cases examined.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.sourceEuropean Signal Processing Conference-
dc.sourceEuropean Signal Processing Conference-
dc.subjectMathematical modelen_US
dc.subjectTime measurementen_US
dc.subjectCovariance matricesen_US
dc.subjectNoise measurementen_US
dc.subjectBayes methodsen_US
dc.titleA minimum variance filter for continuous discrete systems with additive-multiplicative noiseen_US
dc.typeConference Paperen_US
dc.identifier.doihttp://dx.doi.org/10.1109/EUSIPCO.2016.7760665-
dc.relation.isPartOfEuropean Signal Processing Conference-
pubs.finish-date2016-09-02-
pubs.finish-date2016-09-02-
pubs.publication-statusPublished-
pubs.start-date2016-08-29-
pubs.start-date2016-08-29-
Appears in Collections:Dept of Mathematics Research Papers

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