Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/111406
Title: Monte Carlo Methods for Backward Equations in Nonlinear Filtering
Authors: Milstein, G. N.
Tretyakov, M. V.
Issue Date: 2009
Publisher: Cambridge University Press (CUP)
Citation: Milstein G. N. Monte Carlo Methods for Backward Equations in Nonlinear Filtering / G. N. Milstein, M. V. Tretyakov. — DOI 10.3390/plants10122735 // Advances in Applied Probability. — 2009. — Vol. 41. — Iss. 1. — P. 63-100.
Abstract: We consider Monte Carlo methods for the classical nonlinear filtering problem. The first method is based on a backward pathwise filtering equation and the second method is related to a backward linear stochastic partial differential equation. We study convergence of the proposed numerical algorithms.The considered methods have such advantages as a capability in principle to solve filtering problems of large dimensionality, reliable error control, and recurrency. Their efficiency is achieved due to the numerical procedures which use effective numerical schemes and variance reduction techniques. The results obtained are supported by numerical experiments. © Applied Probability Trust 2009.
Keywords: KALLIANPUR-STRIEBEL FORMULA
MEAN-SQUARE AND WEAK NUMERICAL METHODS
MONTE CARLO TECHNIQUE
PATHWISE FILTERING EQUATION
STOCHASTIC PARTIAL DIFFERENTIAL QUATION
KALLIANPUR-STRIEBEL FORMULA
MEAN-SQUARE AND WEAK NUMERICAL METHODS
MONTE CARLO TECHNIQUE
PATHWISE FILTERING EQUATION
STOCHASTIC PARTIAL DIFFERENTIAL QUATION
CONVERGENCE OF NUMERICAL METHODS
NONLINEAR EQUATIONS
NONLINEAR FILTERING
NUMBER THEORY
PARTIAL DIFFERENTIAL EQUATIONS
RANDOM PROCESSES
STOCHASTIC PROGRAMMING
MONTE CARLO METHODS
URI: http://hdl.handle.net/10995/111406
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 67649657680
ISSN: 0001-8678
DOI: 10.3390/plants10122735
metadata.dc.description.sponsorship: Engineering and Physical Sciences Research Council, EPSRC: EP/D049792/1.
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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