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Approximate filters for a nonlinear discrete time filtering problem with small observation noise

Title
Approximate filters for a nonlinear discrete time filtering problem with small observation noise
Type
Article in International Scientific Journal
Year
1994
Authors
Paula Milheiro de Oliveira
(Author)
FEUP
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Journal
The Journal is awaiting validation by the Administrative Services.
Vol. 46
Pages: 1-24
ISSN: 1045-1129
Scientific classification
CORDIS: Technological sciences > Engineering ; Physical sciences > Mathematics > Probability theory ; Physical sciences > Mathematics > Applied mathematics > Engineering mathematics ; Physical sciences > Mathematics > Applied mathematics
Other information
Authenticus ID: P-00P-RZN
Resumo (PT): We study the asymptotic behavior of a nonlinear one-dimensional filtering discrete time problem, as some parameter e tends to 0. Our model can be viewed as a discretization of a nonlinear continuous time problem with smell observation noise. Finite dimensional approximate filters arc proposed and results concerning estimations of their performance are stated and proved. We consider specially the case of both white noises with variance of order 0(r). The proof the result that we give about the error between the approximate filter and the optimal one will make use of probability changes and differentiation with respect to the initial condition. Then we give the main ideas of how to treat other cases, the same kind of proofs allowing us to get to the desired results. For more details on those cases see Milheiro.
Abstract (EN): We study the asymptotic behavior of a nonlinear one-dimensional filtering discrete time problem, as some parameter e tends to 0. Our model can be viewed as a discretization of a nonlinear continuous time problem with smell observation noise. Finite dimensional approximate filters arc proposed and results concerning estimations of their performance are stated and proved. We consider specially the case of both white noises with variance of order 0(r). The proof the result that we give about the error between the approximate filter and the optimal one will make use of probability changes and differentiation with respect to the initial condition. Then we give the main ideas of how to treat other cases, the same kind of proofs allowing us to get to the desired results. For more details on those cases see Milheiro.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 24
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