ON APPLIED DECISION THEORY,

Abstract

This report is based on material from a Stanford University course (EE 252) on the application of statistical decision theory to signal detection, parameter estimation, and pattern recognition. The report is divided into nine parts: (1) Filters and Noise; (2) Sample Value Representation; (3) Detection of a Known Signal in Noise; (4) General Dual-Hypothesis Test; (5) Signal Detection with Mismatched Filters; (6) Detection of Signals with Random Parameters; (7) Test of a Finite Number of Hypothesis; (8) Estimation; (9) Discrete Wiener Filters. Part One provides a general review of classical methods of signal detection and parameter estimation. The rest of the report deals with the application of statistical decision theory to these problems. (Author)

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1962
Accession Number
AD0441210

Entities

People

  • J. Farison
  • N. Abramson

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Decision Theory
  • Detection
  • Materials
  • Pattern Recognition
  • Recognition
  • Signal Detection
  • Statistical Decision Theory
  • Universities

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Technical Research and Report Writing.

Technology Areas

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