Matches in SemOpenAlex for { <https://semopenalex.org/work/W2022023686> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W2022023686 endingPage "508" @default.
- W2022023686 startingPage "493" @default.
- W2022023686 abstract "Summary In treating dynamic systems, sequential Monte Carlo methods use discrete samples to represent a complicated probability distribution and use rejection sampling, importance sampling and weighted resampling to complete the on-line ‘filtering’ task. We propose a special sequential Monte Carlo method, the mixture Kalman filter, which uses a random mixture of the Gaussian distributions to approximate a target distribution. It is designed for on-line estimation and prediction of conditional and partial conditional dynamic linear models, which are themselves a class of widely used non-linear systems and also serve to approximate many others. Compared with a few available filtering methods including Monte Carlo methods, the gain in efficiency that is provided by the mixture Kalman filter can be very substantial. Another contribution of the paper is the formulation of many non-linear systems into conditional or partial conditional linear form, to which the mixture Kalman filter can be applied. Examples in target tracking and digital communications are given to demonstrate the procedures proposed." @default.
- W2022023686 created "2016-06-24" @default.
- W2022023686 creator A5012820890 @default.
- W2022023686 creator A5063514061 @default.
- W2022023686 date "2000-09-01" @default.
- W2022023686 modified "2023-10-08" @default.
- W2022023686 title "Mixture Kalman Filters" @default.
- W2022023686 cites W1513172823 @default.
- W2022023686 cites W1974600023 @default.
- W2022023686 cites W1975911643 @default.
- W2022023686 cites W1977569390 @default.
- W2022023686 cites W1992505333 @default.
- W2022023686 cites W2048796971 @default.
- W2022023686 cites W2054929958 @default.
- W2022023686 cites W2055600978 @default.
- W2022023686 cites W2057487175 @default.
- W2022023686 cites W2064480843 @default.
- W2022023686 cites W2076932885 @default.
- W2022023686 cites W2077611006 @default.
- W2022023686 cites W2085738358 @default.
- W2022023686 cites W2098613108 @default.
- W2022023686 cites W2105934661 @default.
- W2022023686 cites W2114690521 @default.
- W2022023686 cites W2121448470 @default.
- W2022023686 cites W2122512809 @default.
- W2022023686 cites W2126736494 @default.
- W2022023686 cites W2131598171 @default.
- W2022023686 cites W2162898443 @default.
- W2022023686 cites W2332774781 @default.
- W2022023686 cites W2571050459 @default.
- W2022023686 cites W304861154 @default.
- W2022023686 cites W3187867541 @default.
- W2022023686 cites W2152679844 @default.
- W2022023686 doi "https://doi.org/10.1111/1467-9868.00246" @default.
- W2022023686 hasPublicationYear "2000" @default.
- W2022023686 type Work @default.
- W2022023686 sameAs 2022023686 @default.
- W2022023686 citedByCount "520" @default.
- W2022023686 countsByYear W20220236862012 @default.
- W2022023686 countsByYear W20220236862013 @default.
- W2022023686 countsByYear W20220236862014 @default.
- W2022023686 countsByYear W20220236862015 @default.
- W2022023686 countsByYear W20220236862016 @default.
- W2022023686 countsByYear W20220236862017 @default.
- W2022023686 countsByYear W20220236862018 @default.
- W2022023686 countsByYear W20220236862019 @default.
- W2022023686 countsByYear W20220236862020 @default.
- W2022023686 countsByYear W20220236862021 @default.
- W2022023686 countsByYear W20220236862022 @default.
- W2022023686 countsByYear W20220236862023 @default.
- W2022023686 crossrefType "journal-article" @default.
- W2022023686 hasAuthorship W2022023686A5012820890 @default.
- W2022023686 hasAuthorship W2022023686A5063514061 @default.
- W2022023686 hasConcept C105795698 @default.
- W2022023686 hasConcept C11413529 @default.
- W2022023686 hasConcept C126255220 @default.
- W2022023686 hasConcept C150921843 @default.
- W2022023686 hasConcept C154945302 @default.
- W2022023686 hasConcept C157286648 @default.
- W2022023686 hasConcept C19499675 @default.
- W2022023686 hasConcept C206833254 @default.
- W2022023686 hasConcept C33923547 @default.
- W2022023686 hasConcept C41008148 @default.
- W2022023686 hasConcept C43555835 @default.
- W2022023686 hasConcept C52421305 @default.
- W2022023686 hasConcept C52740198 @default.
- W2022023686 hasConceptScore W2022023686C105795698 @default.
- W2022023686 hasConceptScore W2022023686C11413529 @default.
- W2022023686 hasConceptScore W2022023686C126255220 @default.
- W2022023686 hasConceptScore W2022023686C150921843 @default.
- W2022023686 hasConceptScore W2022023686C154945302 @default.
- W2022023686 hasConceptScore W2022023686C157286648 @default.
- W2022023686 hasConceptScore W2022023686C19499675 @default.
- W2022023686 hasConceptScore W2022023686C206833254 @default.
- W2022023686 hasConceptScore W2022023686C33923547 @default.
- W2022023686 hasConceptScore W2022023686C41008148 @default.
- W2022023686 hasConceptScore W2022023686C43555835 @default.
- W2022023686 hasConceptScore W2022023686C52421305 @default.
- W2022023686 hasConceptScore W2022023686C52740198 @default.
- W2022023686 hasIssue "3" @default.
- W2022023686 hasLocation W20220236861 @default.
- W2022023686 hasOpenAccess W2022023686 @default.
- W2022023686 hasPrimaryLocation W20220236861 @default.
- W2022023686 hasRelatedWork W1583020711 @default.
- W2022023686 hasRelatedWork W1824810860 @default.
- W2022023686 hasRelatedWork W1973225318 @default.
- W2022023686 hasRelatedWork W1992819441 @default.
- W2022023686 hasRelatedWork W2126226614 @default.
- W2022023686 hasRelatedWork W2138381686 @default.
- W2022023686 hasRelatedWork W2162253570 @default.
- W2022023686 hasRelatedWork W2381817522 @default.
- W2022023686 hasRelatedWork W2801696468 @default.
- W2022023686 hasRelatedWork W2927378857 @default.
- W2022023686 hasVolume "62" @default.
- W2022023686 isParatext "false" @default.
- W2022023686 isRetracted "false" @default.
- W2022023686 magId "2022023686" @default.
- W2022023686 workType "article" @default.