Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/71535
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Type: Conference paper
Title: Two dimensional recursive optimal smoothing of Gaussian random fields
Author: Carravetta, F.
White, L.
Citation: Proceedings of the 9th IEEE International Conference on Control and Automation (ICCA), held in Santiago, Chile, 19-21 December, 2011: pp.1102-1107
Publisher: IEEE
Publisher Place: USA
Issue Date: 2011
ISBN: 9781457714757
ISSN: 1948-3449
1948-3457
Conference Name: IEEE International Conference on Control and Automation (9th : 2011 : Santiago, Chile)
Statement of
Responsibility: 
Francesco Carravetta and Langford B. White
Abstract: The smoothing problem is considered for a two dimensional (2D) Gaussian Markov field defined on a finite rectangular lattice under Gaussian additive noise. The Gaussian Markov field is assumed to be generated by a (known) local correlation linking each site with the eight sites surrounding it in the lattice. In a former paper it has been shown that for such field (and with a further assumption of homogeneity that we here relax) a 2D realisation can be built up. Such realisation result represents the basis for the present paper, where a 2D-recursive optimal-smoothing algorithm is derived. Even though based on the realisation result, the present paper is nevertheless self-contained.
Rights: © Copyright 2012 IEEE
RMID: 0020118197
DOI: 10.1109/ICCA.2011.6137896
Appears in Collections:Electrical and Electronic Engineering publications

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