Application of Recognition Theory to Missile Identification and Decoy Discrimination. Volume 3. Optimum Decision Boundaries.

Abstract

Statistical classification in n-dimensional space consists in partitioning the space into category regions with decisi n boundaries and assigning an unknown to the category in whose region it falls. The wide utility is demonstrated of a particular form of decisio boundary, the hyper phere, which, while especially easy to implement, is fully optimum for large classes of distributions which may arise in real problems. Of the broad spectrum of distri utions described for which the hypersphere is optimum, particular interest centers on the normal, extended-t, and m-paraboloid distributions; and methods for obtaining the boundary parameters are prescribed. Ordering of the c ordinate directions according to their relative significance in contributing to the decision is examined, therby indicating the most efficient reduction of dimensionality where this may be desired in order to allow further computational simplicity. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 12, 1962
Accession Number
AD0286554

Entities

People

  • Paul W. Cooper

Organizations

  • Melpar

Tags

Communities of Interest

  • Weapons Technologies

DTIC Thesaurus Topics

  • Boundaries
  • Classification
  • Diffraction
  • Discrimination
  • Identification
  • Recognition
  • Social Problems
  • Spectra

Readers

  • Graph Algorithms and Convex Optimization.
  • Snow Cover Descriptors for Reptiles and Their Illustrations.
  • Systems Analysis and Design

Technology Areas

  • Space