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High-Dimensional Fi...
High-Dimensional Filtering Using Nested Sequential Monte Carlo
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- Andersson Naesseth, Christian (författare)
- Linköpings universitet,Statistik och maskininlärning,Tekniska fakulteten
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- Lindsten, Fredrik (författare)
- Linköpings universitet,Statistik och maskininlärning,Tekniska fakulteten
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- Schön, Thomas B., Professor, 1977- (författare)
- Uppsala universitet,Reglerteknik,Uppsala Univ, Sweden
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(creator_code:org_t)
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2019
- 2019
- Engelska.
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Ingår i: IEEE Transactions on Signal Processing. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1053-587X .- 1941-0476. ; 67:16, s. 4177-4188
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Sequential Monte Carlo (SMC) methods comprise one of the most successful approaches to approximate Bayesian filtering. However, SMC without a good proposal distribution can perform poorly, in particular in high dimensions. We propose nested sequential Monte Carlo, a methodology that generalizes the SMC framework by requiring only approximate, properly weighted, samples from the SMC proposal distribution, while still resulting in a correctSMCalgorithm. This way, we can compute an "exact approximation" of, e. g., the locally optimal proposal, and extend the class of models forwhichwe can perform efficient inference using SMC. We showimproved accuracy over other state-of-the-art methods on several spatio-temporal state-space models.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Particle filtering
- spatio-temporal models
- state space models
- approximate Bayesian inference
- backward simulation
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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