A deterministic discretisation-step upper bound for state estimation via Clark transformations

Simple item page
dc.contributor.authorMalcolm, W.
dc.contributor.authorElliott, R.
dc.contributor.authorVan Der Hoek, J.
dc.date.issued2004
dc.descriptionCopyright © 2004 Hindawi Publishing Corporation
dc.description.abstractWe consider the numerical stability of discretisation schemes for continuous-time state estimation filters. The dynamical systems we consider model the indirect observation of a continuous-time Markov chain. Two candidate observation models are studied. These models are (a) the observation of the state through a Brownian motion, and (b) the observation of the state through a Poisson process. It is shown that for robust filters (via Clark's transformation), one can ensure nonnegative estimated probabilities by choosing a maximum grid step to be no greater than a given bound. The importance of this result is that one can choose an a priori grid step maximum ensuring nonnegative estimated probabilities. In contrast, no such upper bound is available for the standard approximation schemes. Further, this upper bound also applies to the corresponding robust smoothing scheme, in turn ensuring stability for smoothed state estimates.
dc.description.statementofresponsibilityW. P. Malcolm, R. J. Elliott, and J. van der Hoek
dc.identifier.citationJournal of Applied Mathematics and Stochastic Analysis, 2004; 2004(4):371-384
dc.identifier.doi10.1155/S1048953304311032
dc.identifier.issn1048-9533
dc.identifier.issn2090-3340
dc.identifier.urihttp://hdl.handle.net/2440/467
dc.language.isoen
dc.publisherNorth Atlantic Science Publishing Company
dc.source.urihttps://doi.org/10.1155/s1048953304311032
dc.titleA deterministic discretisation-step upper bound for state estimation via Clark transformations
dc.typeJournal article
pubs.publication-statusPublished

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
hdl_467.pdf
Size:
197.98 KB
Format:
Adobe Portable Document Format
Download

Collections

Applied Mathematics publications