Estimation of Probability Density Using Signature Tables for Application to Pattern Recognition

Abstract

Signature table training method consists of cumulative evaluation of a function (such as a probability density) at pre-assigned co-ordinate values of input parameters to the table. The training is conditional; based on a binary valued learning input to a table which is compared to the label attached to each training sample. Interpretation of an unknown sample vector is then equivalent of a table look-up, i.e. extraction of the function value stored at the proper co-ordinates. Such a technique is very useful when a large number of samples must be interpreted as in the case of speech recognition and the time required for the training as well as for the recognition is at a premium.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1973
Accession Number
AD0763611

Entities

People

  • R. B. Thosar

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automated Speech Recognition
  • Boundaries
  • Classification
  • Computer Science
  • Hierarchies
  • Learning
  • Pattern Recognition
  • Probability
  • Probability Density Functions
  • Probability Distributions
  • Random Variables
  • Recognition
  • Test And Evaluation

Fields of Study

  • Computer science

Readers

  • Geodesy
  • Neural Network Machine Learning.
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference