PATTERN RECOGNITION AND DETECTION BY MACHINE

Abstract

Pattern recognition is considered generally, but emphasis is placed on the following points: optimum estimation of statistical parameters so as to minimize the probability of incorrect classification, non-Gaussian and non-stationary situations, pattern detection in a continuing time series and calculation of error probabilities. Some of the work is specifically directed toward the problem of radio station recognition. A design procedure for pattern recognizing machines is suggested which uses results from this report and other referenced sources.

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Document Details

Document Type
Technical Report
Publication Date
Mar 08, 1963
Accession Number
AD0418387

Entities

People

  • Arthur E. Laemmel

Organizations

  • New York University Tandon School of Engineering

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Calibration
  • Detection
  • Detectors
  • Engineering
  • Filters
  • Game Theory
  • Matched Filters
  • Mathematical Models
  • Operations Research
  • Pattern Recognition
  • Probability
  • Probability Density Functions
  • Radio Stations
  • Random Variables
  • Recognition
  • Stochastic Processes

Readers

  • Aerospace Test and Evaluation
  • Neural Network Machine Learning.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference