Optimal Stationary Behavior in Some Stochastic Nonlinear Filtering Problems- A Bound Approach.

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dc.contributor.authorSaydy, L.en_US
dc.contributor.authorBlankenehip, Gilmer L.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:39:22Z
dc.date.available2007-05-23T09:39:22Z
dc.date.issued1987en_US
dc.description.abstractA lower and upper bound on the a priori optimal mean square error is used to study the stationary behavior of one dimensional nonlinear filters. The long time behavior as t--> INFINITY for asymptotically linear systems is investigated. Lower and upper bounds of the Riccati type are derived and it is shown that for nonlinear systems with linear limiting ones, the Kalman filter (KF) formally designed for the limiting systems is asymptotically optimal in some sense. Examples with simulation results are provided.en_US
dc.format.extent918298 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/4689
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1987-184en_US
dc.titleOptimal Stationary Behavior in Some Stochastic Nonlinear Filtering Problems- A Bound Approach.en_US
dc.typeTechnical Reporten_US

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