Experiments with the Back Propagation Algorithm: A Systematic Look at a Small Problem.

Abstract

A multi-layer perception is a type of feed neural network for which there exists a learning algorithm based on error back-propagation. Experimental results are presented of the use of this error back-propagation algorithm on a carefully selected, simple problem. The effects of varying the structure of the network, the number of hidden units, the size of the training set and the initial weight values have been investigated. A number of ways of analysing solutions to such a simple problem are demonstrated. Explanations of the observed behaviour are offered which may provide insights applicable to a range of problems.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 29, 1987
Accession Number
ADA189266

Entities

People

  • J. S. Bridle
  • M. D. Bedworth

Organizations

  • Royal Signals and Radar Establishment

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence Software
  • Automated Speech Recognition
  • Cognitive Science
  • Detectors
  • Foreign Languages
  • Hidden Markov Models
  • Image Processing
  • Learning
  • Markov Models
  • Models
  • Neural Networks
  • Pattern Recognition
  • Probability
  • Recognition
  • Training
  • Transitions

Fields of Study

  • Computer science

Readers

  • Calculus or Mathematical Analysis
  • Neural Network Machine Learning.
  • Regression Analysis.

Technology Areas

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