Two dimensional recursive optimal smoothing of Gaussian random fields

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dc.contributor.authorCarravetta, F.
dc.contributor.authorWhite, L.
dc.contributor.conferenceIEEE International Conference on Control and Automation (9th : 2011 : Santiago, Chile)
dc.date.issued2011
dc.description.abstractThe smoothing problem is considered for a two dimensional (2D) Gaussian Markov field defined on a finite rectangular lattice under Gaussian additive noise. The Gaussian Markov field is assumed to be generated by a (known) local correlation linking each site with the eight sites surrounding it in the lattice. In a former paper it has been shown that for such field (and with a further assumption of homogeneity that we here relax) a 2D realisation can be built up. Such realisation result represents the basis for the present paper, where a 2D-recursive optimal-smoothing algorithm is derived. Even though based on the realisation result, the present paper is nevertheless self-contained.
dc.description.statementofresponsibilityFrancesco Carravetta and Langford B. White
dc.identifier.citationProceedings of the 9th IEEE International Conference on Control and Automation (ICCA), held in Santiago, Chile, 19-21 December, 2011: pp.1102-1107
dc.identifier.doi10.1109/ICCA.2011.6137896
dc.identifier.isbn9781457714757
dc.identifier.issn1948-3449
dc.identifier.issn1948-3457
dc.identifier.orcidWhite, L. [0000-0001-6660-0517]
dc.identifier.urihttp://hdl.handle.net/2440/71535
dc.language.isoen
dc.publisherIEEE
dc.publisher.placeUSA
dc.rights© Copyright 2012 IEEE
dc.source.urihttps://doi.org/10.1109/icca.2011.6137896
dc.titleTwo dimensional recursive optimal smoothing of Gaussian random fields
dc.typeConference paper
pubs.publication-statusPublished

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