THEORETICAL FRAMEWORKS FOR PATTERN RECOGNITION PROBLEMS.

Abstract

This report summarizes several studies conducted on pattern recognition problems. One of these involved two problems of parametric statistics with a view to their application to nonsupervised pattern recognition. Another examined the question of the least costly word equivalent to a given word in the case in semigroups in which the equivalence relation is a two-sided congruence relation. A third continues a study of current flow in the central nervous system. The quantitative relationship between the parameter of stimulus current intensity and the anatomical characteristics of certain neural elements in the nervous system was examined. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1967
Accession Number
AD0666473

Entities

People

  • Wilson P. Tanner Jr

Organizations

  • University of Michigan

Tags

DTIC Thesaurus Topics

  • Anatomy
  • Biological Sciences
  • Central Nervous System
  • Data Science
  • Identification
  • Intensity
  • Nervous System
  • Pattern Recognition
  • Recognition
  • Statistics

Fields of Study

  • Psychology

Readers

  • Mathematical Modeling and Probability Theory.
  • Speech Processing/Speech Recognition.
  • Theoretical Analysis.

Technology Areas

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