Statistical classification based on observations of random Gaussian fields

Abstract

The problem of classification of objects located in domain D ⊂ R2 based on observations of random Gaussian fields with a factorized covariance function is considered. The first‐order asymptotic expansion for the expected error regret is presented. Obtained numerical results allow us to compare suggested expansion for some widely applicable models of spatial covariance function. Statistinis klasifikavimas remiantis atsitiktinių Gauso laikų stebėjimais Santrauka Nagrinejamas uždavinys apie objektu iš srites D C R 2 klasifikavima, remiantis atsitiktiniu Gauso lauku stebejimais. Pateikti asimptotiniai laukiamos paklaidos iverčiai. Atlikus skaitinio modeliavimo eksperimenta naujasis skleidinys lyginamas su kitais žinomais skleidimais. First Published Online: 14 Oct 2010

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