PATTERN RECOGNITION WITH SELF-ORGANIZING MACHINES

Abstract

Most of the pattern-recognition self-organizing machines can be classified as adjustable-weight threshold-logic machines, statistical-switching machines, or correlation machines. A noisy pattern is a pattern that varies slightly from a model pattern that the machine has been taught. Computer simulations of a typical machine from each of three classes indicate that the noisy pattern recognition capabilities are poor for statistical-switching machines, good for threshold-logic machines, best for correlation type machines. A proposed correlation self-organizing machine is simple, learns in one step, and recog nizes noisy patterns accurately.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1963
Accession Number
AD0419094

Entities

People

  • Alling C. Foreman

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Computer Programming
  • Computer Programs
  • Computer Simulations
  • Computers
  • Correlation Techniques
  • Digital Computers
  • Electrical Engineering
  • Language
  • Logic
  • Logic Gates
  • Mathematical Analysis
  • Mathematical Models
  • Models
  • Multivibrators
  • Pattern Recognition
  • Simulations

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Neural Networks