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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/933178

Title: A discrete nonlinear filter for fast sampled problems based on vector quantization
Author/Creator: Cea, Mauricio G.; Goodwin, Graham C.; Feuer, Arie
Institution: The University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science
Description: he Chapman-Kolmogorov equation and Bayes’ rule provide a conceptually simple solution to the discrete nonlinear filtering problem. Unfortunately these equations involve high order multiple integrals which are, in general, computationally intractable. Here we exploit recent results on an incremental form of the discrete nonlinear filter to develop a novel algorithm which is computationally straightforward at high sample rates.We illustrate performance by a two examples.
Relation: 2010 American Control Conference (ACC2010). Proceedings of the 2010 American Control Conference (Baltimore, MD 30 June - 2 July, 2010) p. 1399-1403
Relation: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5530513
Date: 2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Keyword(s): Bayes methods; integral equations; nonlinear filters; vector quantisation
Resource Type: conference paper
Identifier: http://hdl.handle.net/1959.13/933178
Identifier: ISBN:9781424474264
Identifier: ISSN:0743-1619

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