Accession Number : ADA263735
Title : Mixed Limit Theorems for Pattern Analysis.
Descriptive Note : Technical rept.,
Corporate Author : FLORIDA STATE UNIV TALLAHASSEE DEPT OF STATISTICS
Personal Author(s) : Grenander, Ulf ; Sethuraman, Jayaram
Report Date : FEB 1993
Pagination or Media Count : 17
Abstract : Limit theorems are derived for probability measures of random configurations over graphs which are used as prior distributions in pattern theory. For one-dimensional graphs, these limits can be viewed as distributions of certain stochastic processes, while in higher dimensions the limits will in some cases have to be interpreted as belonging to Schwartz distributions. Such limit distributions are easy to use in pattern analysis, and greatly reduce the computing effort required in comparison with stochastic relaxation methods.
Descriptors : *PATTERN RECOGNITION, *BAYES THEOREM, GRAPHS, CONFIGURATIONS, ONE DIMENSIONAL, COMPUTATIONS, CONVERGENCE.
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE