Application of Automatic Clustering to Emitter Identification

Abstract

The goal of clustering is the partitioning of a given set of objects into subsets called clusters in such a way that the objects in a cluster are similar to one another and that objects in different clusters are dissimilar. Clustering may help in getting a more or less direct understanding of the relationships among the objects, and it may be useful as a first step in pattern recognition. Some possible applications are automatic phoneme recognition, data base management systems, personnel classification, detection of errors in files and computer security. Several clustering methods were applied to data sets of practical importance. Automatic pattern recognition using the k nearest neighbors was applied. An efficient method for selecting a good subset from the full of 44 features was tried. In all cases, the results were good. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1976
Accession Number
ADA033916

Entities

People

  • James Slagle
  • Richard C. Lee

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Automatic
  • Classification
  • Clustering
  • Communication Systems
  • Computer Science
  • Computers
  • Cybersecurity
  • Data Sets
  • Databases
  • Detection
  • Emitters
  • Identification
  • Pattern Recognition
  • Recognition
  • Security

Fields of Study

  • Computer science

Readers

  • Computer Vision.

Technology Areas

  • AI & ML
  • Cyber