Statistical Methods in Search.

Abstract

This work consists of the development of a number of statistical techniques useful in solving search problems. Among these are the employment of Bayesian, minimax, and maximum likelihood inferential techniques in the estimation of the position of a moving target during a search. An application of potential theory to search problems is also considered.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1978
Accession Number
ADA058031

Entities

People

  • Thomas L. Corwin

Organizations

  • Johns Hopkins University

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Bayesian Inference
  • Bayesian Networks
  • Computers
  • Data Science
  • Estimators
  • Information Processing
  • Information Science
  • Markov Chains
  • Maximum Likelihood Estimation
  • Moving Targets
  • Probability
  • Probability Distributions
  • Random Variables
  • Statistical Algorithms
  • Statistical Inference
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Artificial Intelligence
  • Sensor Fusion and Tracking Systems.

Technology Areas

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