STUDY OF NEUROTRON NETWORKS IN LEARNING AUTOMATA.

Abstract

Extensive data and mathematical theory are presented on the computer simulation or Probability State Variable (PSV) devices, e.g., the Neurotron, Random State Variable (RSV) Strategy devices, and networks of these elements as a function of the network connectivity, and score and value functions in four problem classes: re-entry trajectory prediction, pattern recognition, inferential measurement techniques, and self-organizing controllers. The simulation models are presented in detail. Hardware implementation is discussed, using statistical source design as a vehicle for insight into cost analysis of the Demonstrator Neurotron and the feasibility of construction of the networks studied. (Author)

Document Details

Document Type
Technical Report
Publication Date
Feb 06, 1965
Accession Number
AD0455688

Entities

People

  • R. E. J. Moddes

Tags

DTIC Thesaurus Topics

  • Automata
  • Computer Simulations
  • Computers
  • Construction
  • Cost Analysis
  • Costs
  • Learning
  • Measurement
  • Pattern Recognition
  • Probability
  • Recognition
  • Simulations
  • Simulators
  • Trajectories

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computer Engineering
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference