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Two Dimensional Recursive Optimal Smoothing of Gaussian Random Fields

Conference Paper
Publication Date:
2011
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.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Markov fields; Smoothing; Stochastic Processes
List of contributors:
Carravetta, Francesco
Authors of the University:
CARRAVETTA FRANCESCO
Handle:
https://iris.cnr.it/handle/20.500.14243/224843
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