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Discrete-Time Filtering for Linear Systems in Correlated Noise with Non-Gaussian Initial Conditions.

dc.contributor.authorSowers, R.B.en_US
dc.contributor.authorMakowski, Armand M.en_US
dc.date.accessioned2007-05-23T09:42:07Z
dc.date.available2007-05-23T09:42:07Z
dc.date.issued1988en_US
dc.identifier.urihttp://hdl.handle.net/1903/4811
dc.description.abstractWe consider the one-step prediction problem for discrete-time linear systems in correlated plants and observation noises, and non-Gaussian initial conditions. Explicit representations are obtained for the MMSE and LMMSE (or Kalman) estimates of the state given past observations, as well as for the expected square of their difference. These formulae are obtained with the help of the Girsanov transformation for Gaussian white noise sequences, and display explicitly the dependency of the quantities of interest on the initial distribution. Applications of these results can be found in [5] and [6].en_US
dc.format.extent630804 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1988-85en_US
dc.titleDiscrete-Time Filtering for Linear Systems in Correlated Noise with Non-Gaussian Initial Conditions.en_US
dc.typeTechnical Reporten_US
dc.contributor.departmentISRen_US


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