Adaptive Neural Network Models for Intelligent Computations.

Abstract

By looking closely at the dynamics of learning, it was discovered that for different input the states of network tended to cluster around three values plus the initial state. These four states can be considered as possible states of an actual finite state machine and the movement between these states as a function of input can be interpreted as the state transition of a state machine. This four state machine constructed is a perfect state machine that recognize the dual parity grammar. It recognizes dual parity strings with arbitrary length. This rule extraction generalization power is qualitatively different from that of the 'data interpolation' paradigm which is usually true for a feedforward neural net.

Document Details

Document Type
Technical Report
Publication Date
Dec 31, 1991
Accession Number
ADA254689

Entities

People

  • G. Z. Sun
  • H. H. Chen
  • Y. C. Lee

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence Computing
  • Artificial Intelligence Software
  • Computations
  • Dynamics
  • Extraction
  • Interpolation
  • Learning
  • Neural Networks
  • Transitions

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Programming and Software Development.
  • Neural Network Machine Learning.

Technology Areas

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