Study Program of Pattern Recognition Research

Abstract

The basic element in the solution of pattern recognition problems is a requirement for the capability to recognize membership in classes. This report considers the automatic establishment of decision criteria for measuring membership in classes that are known only from a finite set of samples. Each sample is represented by a point in a suitably chosen, finite-dimensional vector space in which a class corresponds to a domain that contains its samples. Boundaries of the domain in the vector space can be expressed analytically with the aid of transformations that cluster samples of a class and separate classes from one another. From these geometrical notions a generalized discriminant analysis is developed which, as the sample size goes to infinity, leads to decision-making that is consistent with the results of statistical decision theory.

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Document Details

Document Type
Technical Report
Publication Date
Dec 31, 1961
Accession Number
AD0273235

Entities

People

  • Alice K. Hartley
  • George S. Sebestyen

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Computational Science
  • Computers
  • Decision Theory
  • Detection
  • Discriminant Analysis
  • Distribution Functions
  • Equations
  • Information Science
  • Monte Carlo Method
  • Normal Distribution
  • Notation
  • Pattern Recognition
  • Probability
  • Random Variables
  • Statistical Decision Theory

Readers

  • Computational Linguistics
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space
  • Space - Space Objects