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Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/135574
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dc.contributor.authorLiu, W.-
dc.contributor.authorShi, P.-
dc.contributor.authorZhang, H.-
dc.date.issued2022-
dc.identifier.citationJournal of Computational and Applied Mathematics, 2022; 408:114138-1-114138-19-
dc.identifier.issn0377-0427-
dc.identifier.issn1879-1778-
dc.identifier.urihttps://hdl.handle.net/2440/135574-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityWei Liu, Peng Shi, Huiyan Zhang-
dc.language.isoen-
dc.publisherElsevier BV-
dc.rights© 2022 Elsevier B.V. All rights reserved.-
dc.subjectKalman filtering; Discrete-time; Linear systems; Finite-step autocorrelated; Convergence-
dc.titleKalman filtering with finite-step autocorrelated measurement noise-
dc.typeJournal article-
dc.identifier.doi10.1016/j.cam.2022.114138-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP170102644-
pubs.publication-statusPublished-
dc.identifier.orcidShi, P. [0000-0001-8218-586X]-
Appears in Collections:Mathematical Sciences publications

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