Mathematical Programming Applications in Pattern Recognition.

Abstract

Problems in pattern recognition are treated by the methods of mathematical programming. In particular the two-class pattern classification model with decision rules based on discriminant functions is considered with emphasis on mathematical programs that determine linear and piecewise linear discriminants. For linearly separable pattern sets of separating hyperplane can be determined by solving a system of linear inequalities. This system serves as the constraint set for a class of mathematical programs that define separating linear discriminants exhibiting maximum tolerance to pattern noise. Specific cases that can be modelled as linear and quadratic programs are discussed and a reliability interpretation of the objective criterion is given.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1978
Accession Number
ADA061496

Entities

People

  • Robert Hemstreet Leary

Organizations

  • Stanford University

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Aspect Ratio
  • Computer Programming
  • Computer Programs
  • Feature Extraction
  • Linear Programming
  • Mathematical Programming
  • New York
  • Operations Research
  • Pattern Recognition
  • Probability
  • Recognition
  • Regression Analysis
  • Reliability
  • Simplex Method
  • Training

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Mathematical Modeling and Probability Theory.
  • Neural Network Machine Learning.

Technology Areas

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