Accession Number : AD0640494
Title : NONSUPERVISED ADAPTIVE DETECTION FOR MULTIVARIATE NORMAL DISTRIBUTIONS.
Descriptive Note : Final rept., Feb 65-Apr 66,
Corporate Author : SYLVANIA ELECTRONIC SYSTEMS-EAST WALTHAM MASS
Personal Author(s) : Cooper,Paul W.
Report Date : SEP 1966
Pagination or Media Count : 84
Abstract : Nonsupervised adaptive detection for categories described statistically by multivariate normal distributions is approached as a problem in multi-parameter estimation for a multi-modal distribution. Nonsupervised learning consists in estimating the component probability distributions of a mixture of distributions, given a sequence of samples known only to have been drawn from the over-all mixture. This report considers the two-category case involving general unequal covariance matrices and the multiple-category case for spherically symmetric distributions. The techniques provided are applicable to problems in statistical classification, pattern recognition, and signal detection. (Author)
Descriptors : (*DECISION THEORY, *MULTIVARIATE ANALYSIS), STATISTICAL DISTRIBUTIONS, MATRICES(MATHEMATICS), PATTERN RECOGNITION, DETECTION
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE