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Accession Number:
AD0441210
Title:
ON APPLIED DECISION THEORY,
Descriptive Note:
Corporate Author:
STANFORD UNIV CA STANFORD ELECTRONICS LABS
Report Date:
1962-09-01
Pagination or Media Count:
82.0
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
Distribution Statement:
APPROVED FOR PUBLIC RELEASE