Normalization of Spectrum Analyzer Output Data.

Abstract

Two results are developed in this paper. First, it is shown that nothing is to be gained by single-sample likelihood ratio processing. Although this is an intuitively apparent fact it never hurts to verify such assertions. The other result is that it is possible to theoretically predict the performance of the joint likelihood ratio data reduction criterion under quiet realistic assumptions concerning the noise and signals. Therefore, equations can be evaluated numerically and receiver operating characteristic (ROC) curves can be obtained. These curves can be compared to the (ROC) curves that are obtained both theoretically and experimentally from the simple OR-Gating data reduction technique.

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Document Details

Document Type
Technical Report
Publication Date
Dec 12, 1969
Accession Number
ADA051397

Entities

Organizations

  • Tracor

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Ambient Noise
  • Analyzers
  • Data Reduction
  • Detection
  • Detectors
  • Distribution Functions
  • False Alarms
  • Frequency
  • Frequency Analyzers
  • Gaussian Processes
  • Narrowband
  • Noise
  • Probability
  • Random Variables
  • Spectra
  • Spectrum Analyzers
  • Warning Systems

Readers

  • Educational Psychology
  • Neural Network Machine Learning.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference