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dc.contributor.authorAhmed, N. U.en
dc.contributor.authorCharalambous, Charalambos D.en
dc.creatorAhmed, N. U.en
dc.creatorCharalambous, Charalambos D.en
dc.description.abstractIn this paper we study continuous time filtering for linear systems driven by fractional Brownian motion processes. We present the derivation of the optimum linear filter equations which involve a pair of functional-differential equations giving the error co-variance (matrix-valued) function and the filter. These equations are the appropriate substitutes of the matrix-Riccati differential equation arising in classical Kalman filtering. However the optimum filter has the classical appearance and, as usual, it is driven by the increments of the observed process. Our derivation is based on the same general principles as used in [5,6,7].en
dc.sourceProceedings of the IEEE Conference on Decision and Controlen
dc.sourceProceedings of the IEEE Conference on Decision and Controlen
dc.subjectMathematical modelsen
dc.subjectRandom processesen
dc.subjectLinear control systemsen
dc.subjectRiccati equationsen
dc.subjectBrownian movementen
dc.subjectKalman filteringen
dc.subjectFractional brownian motionen
dc.subjectOptimum linear filter equationsen
dc.titleFiltering for linear systems driven by fractional Brownian motionen
dc.description.endingpage4263Πολυτεχνική Σχολή / Faculty of EngineeringΤμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering
dc.type.uhtypeConference Objecten
dc.contributor.orcidCharalambous, Charalambos D. [0000-0002-2168-0231]

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