LEARNING IN PATTERN RECOGNITION

Abstract

This technical note deals with the study of optimum learning in pattern recognition problems. The class of pattern recognition problems which is treated is perfectly general and the results may be appled to patterns of visual, aural or electromagnetic origin. Mathematical solutions are derived and practical instrumentation of these solutions are suggested for the following pattern recognition situations: (1) recognition of fixed a priori known patterns immersed in additive gaussian noise, (2) recognition of unknown fixed patterns immered in additive gaussian noise, (3) recognition of patterns drawn from a gaussian ensemble with known mean and covariance and immersed in additive gaussian noise, (4) learning in pattern recognition, (5) learning without a teacher, and (6) recognition of unknown patterns which vary in time (pattern tracking). (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1961
Accession Number
AD0267798

Entities

People

  • N. Abramson

Organizations

  • ITT Corporation

Tags

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Covariance
  • Gaussian Noise
  • Instrumentation
  • Learning
  • Noise
  • Pattern Recognition
  • Recognition

Readers

  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Speech Processing/Speech Recognition.
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks