APPLICATION OF WIENER CANONICAL EXPANSIONS TO PATTERN RECOGNITION. VOLUME I.

Abstract

The investigations centered upon the following areas of research: An examination of the existence, convergence, and ergodicity properties of Wiener Canonical Expansions of Bayes rules, for the purpose of specifying the class of stochastic processes that can be treated by this procedure; A study of the effects of truncating the expansions to enable recognition of stochastic processes in a practical, physically realizable form; A comparison of the method with other approaches for describing the recognition of temporal waveforms; Extensions of the basic expansion procedure for synthesizing nonlinear systems to multiple input-output systems and discrete-logic systems. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 30, 1970
Accession Number
AD0705674

Entities

People

  • Alan L. Citron
  • Donald B. Brick
  • Ernest G. Henrichon
  • R. W. Stout

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Convergence
  • Ergodic Processes
  • Identification
  • Nonlinear Systems
  • Pattern Recognition
  • Recognition
  • Stochastic Processes
  • Waveforms

Readers

  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Mathematical Modeling and Probability Theory.
  • Neural Network Machine Learning.

Technology Areas

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