Risk Sensitive Filtering with Poisson Process Observations

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dc.contributor.authorMalcolm, W Paul
dc.contributor.authorJames, Matthew
dc.contributor.authorElliott, Robert J
dc.date.accessioned2015-12-13T23:17:58Z
dc.date.issued2000
dc.date.updated2015-12-12T08:55:02Z
dc.description.abstractIn this paper we consider risk sensitive filtering for Poisson process observations. Risk sensitive filtering is a type of robust filtering which offers performance benefits in the presence of uncertainties. We derive a risk sensitive filter for a stochastic system where the signal variable had dynamics described by a diffusion equation and determines the rate function for an observation process. The filtering equations are stochastic integral equations. Computer simulations are presented to demonstrate the performance gain for the risk sensitive filter compared with the risk neutral filter.
dc.identifier.issn0095-4616
dc.identifier.urihttp://hdl.handle.net/1885/89950
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE Inc)
dc.sourceApplied Mathematics and Optimization
dc.subjectKeywords: Computer simulation; Integral equations; Partial differential equations; Poisson distribution; Signal filtering and prediction; Theorem proving; Change of measure; Martingale calculus; Point processes; Poisson process; Risk sensitive filtering; Markov pro
dc.titleRisk Sensitive Filtering with Poisson Process Observations
dc.typeJournal article
local.bibliographicCitation.lastpage402
local.bibliographicCitation.startpage387
local.contributor.affiliationMalcolm, W Paul, National ICT Australia
local.contributor.affiliationJames, Matthew, College of Engineering and Computer Science, ANU
local.contributor.affiliationElliott, Robert J, University of Calgary
local.contributor.authoremailu9109947@anu.edu.au
local.contributor.authoruidJames, Matthew, u9109947
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor080105 - Expert Systems
local.identifier.ariespublicationMigratedxPub20194
local.identifier.citationvolume41
local.identifier.scopusID2-s2.0-0033886252
local.identifier.uidSubmittedByMigrated
local.type.statusPublished Version

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