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