2018 21st International Conference on Information Fusion (FUSION) 2018
DOI: 10.23919/icif.2018.8455704
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Reduced Order Nonlinear Filters for Multi-Scale Systems with Correlated Sensor Noise

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Cited by 4 publications
(8 citation statements)
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“…Finally, the first term in (14b) is built after the Gubinelli derivative from (12). Crucially, the scheme (14) takes the lifted component ∆Y k (representing iterated integrals of the path (Yt) t≥0 ) as an input. This dependence allows our methodology to appropriately take into account multiscale structure and other information encoded in the signature, but also necessitates appropriate ways to estimate Y k from data.…”
Section: Setting and Main Resultsmentioning
confidence: 99%
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“…Finally, the first term in (14b) is built after the Gubinelli derivative from (12). Crucially, the scheme (14) takes the lifted component ∆Y k (representing iterated integrals of the path (Yt) t≥0 ) as an input. This dependence allows our methodology to appropriately take into account multiscale structure and other information encoded in the signature, but also necessitates appropriate ways to estimate Y k from data.…”
Section: Setting and Main Resultsmentioning
confidence: 99%
“…Itô, Stratonovich and rough integrals. Before concluding this introduction, let us comment on the difference between the RP-EnKF scheme (14) and the more conventional EnKF updates…”
Section: Setting and Main Resultsmentioning
confidence: 99%
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