Accession Number:

AD0441210

Title:

ON APPLIED DECISION THEORY,

Descriptive Note:

Corporate Author:

STANFORD UNIV CA STANFORD ELECTRONICS LABS

Personal Author(s):

• Abramson, N.
• Farison, J.

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

Descriptors:

• *DECISION THEORY
• DETECTION
• PATTERN RECOGNITION
• MATCHED FILTERS
• DATA PROCESSING
• NOISE(RADAR)
• SIGNAL TO NOISE RATIO
• RADAR SIGNALS
• RADAR INTERCEPTION

Subject Categories:

Distribution Statement:

APPROVED FOR PUBLIC RELEASE