ON THE APPLICABILITY OF WIENER'S CANONICAL EXPANSIONS.

Abstract

In previous papers, the application of Wiener's Hermite-Laguerre expansion procedure to the multiple-alternative discrete-decision problem, with learning, characteristic of many pattern recognition problems was proposed. The applicability to problems in cybernetics, intelligence, and learning of the resulting Bayes' type system was discussed. In the present paper the results of a subsequent analytical investigation which included a digital simulation of the procedure are summarized. Emphasis is on the aspects of realizability, convergence, and applicability of the method as regards the classes of stochastic inputs for which the procedure is valid. (Author)

Document Details

Document Type
Technical Report
Publication Date
Mar 20, 1967
Accession Number
AD0650193

Entities

People

  • Donald B. Brick

Tags

DTIC Thesaurus Topics

  • Convergence
  • Cybernetics
  • Identification
  • Learning
  • Pattern Recognition
  • Recognition
  • Simulations

Readers

  • Calculus or Mathematical Analysis
  • Neural Network Machine Learning.

Technology Areas

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