On a role of predictor in the filtering stability

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dc.creatorChigansky, P.
dc.creatorLiptser, R.
dc.date2005-04-06
dc.date2006-07-17
dc.date.accessioned2026-07-07T06:39:43Z
dc.date.available2026-07-07T06:39:43Z
dc.descriptionWhen is a nonlinear filter stable with respect to its initial condition? In spite of the recent progress, this question still lacks a complete answer in general. Currently available results indicate that stability of the filter depends on the signal ergodic properties and the observation process regularity and may fail if either of the ingredients is ignored. In this note we address the question of stability in a particular weak sense and show that the estimates of certain functions are always stable. This is verified without dealing directly with the filtering equation and turns to be inherited from certain one-step predictor estimates.
dc.descriptionthe final version
dc.identifierhttps://arxiv.org/abs/math/0504094
dc.identifierhttp://arxiv.org/abs/math/0504094
dc.identifierElectr. Comm. in Probab. 11 (2006) pp. 129--140
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/101180
dc.subjectProbability
dc.subjectDynamical Systems
dc.subject93E11; 60J57
dc.titleOn a role of predictor in the filtering stability
dc.typetext

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