Adaptive Resonance Theory 1

Abstract

This report describes the function, operation, test and evaluation of a Neural Network that accomplishes unsupervised learning of binary input patterns by classifying them using Adaptive Resonance Theory. Keywords: Machine learning; Artificial intelligence; Speech recognition; Character recognition; Pattern recognition; Acoustic differentiation; Detection; Adaptive filters; Pattern classification; Unsupervised learning; Neural network.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1989
Accession Number
ADA219044

Entities

People

  • Scott S. Shyne

Organizations

  • Rome Laboratory

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Computer Programming
  • Computer Science
  • Computers
  • Differential Equations
  • Equations
  • Heat Of Activation
  • Machine Learning
  • Mathematical Analysis
  • Neural Networks
  • Numbers
  • Security
  • Test And Evaluation
  • Unsupervised Machine Learning

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Neural Network Machine Learning.

Technology Areas

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