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Nonlinear Filtering with Fractional Brownian Motion

dc.contributor.authorAmirdjanova,en_US
dc.date.accessioned2006-09-08T20:16:22Z
dc.date.available2006-09-08T20:16:22Z
dc.date.issued2002-12-19en_US
dc.identifier.citationAmirdjanova,; (2002). "Nonlinear Filtering with Fractional Brownian Motion ." Applied Mathematics & Optimization 46 (2-3): 81-88. <http://hdl.handle.net/2027.42/42375>en_US
dc.identifier.issn0095-4616en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/42375
dc.description.abstractAbstract. Our objective is to study a nonlinear filtering problem for the observation process perturbed by a Fractional Brownian Motion (FBM) with Hurst index 1/2 <H<1 . A reproducing kernel Hilbert space for the FBM is considered and a ``fractional'' Zakai equation for the unnormalized optimal filter is derived.en_US
dc.format.extent93190 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherSpringer-Verlag; Springer-Verlag New York Inc.en_US
dc.subject.otherLegacyen_US
dc.subject.otherKey Words. Nonlinear Filtering, Fractional Brownian Motion, Reproducing Kernel Hilbert Space, Stochastic Differential Equations. AMS Classification. 60H20, 60G15, 60G35.en_US
dc.titleNonlinear Filtering with Fractional Brownian Motionen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelIndustrial and Operations Engineeringen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Statistics, University of Michigan, Ann Arbor, MI 48109-1092, USA, USen_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/42375/1/20460081.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s00245-002-0754-2en_US
dc.identifier.sourceApplied Mathematics & Optimizationen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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