Neural Network Learning Systems: An Overview,

Abstract

Neural Network Learning Systems are models which are loosely inspired by notions of how self-organization and learning in biological systems might occur. These models are closely related to many established pattern recognition, classification, and regression techniques. Many exciting applications of these methods are being pursued, including nervous system modeling, robotics, signal processing, zipcode and speech recognition, speech production, computer backgammon, and financial analysis. This short paper is intended as a pointer to some of the vast literature covering this field.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007169

Entities

People

  • John E. Moody

Organizations

  • Yale University

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Automata Theory
  • Automated Speech Recognition
  • Computer Science
  • Computers
  • Dimensionality Reduction
  • Engineering
  • Learning
  • Nervous System
  • Neural Networks
  • Pattern Recognition
  • Recognition
  • Robotics
  • Self Organizing Systems
  • Signal Processing
  • Systems Biology

Fields of Study

  • Computer science

Readers

  • Neural Network Machine Learning.
  • Software Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks
  • Autonomy