On the Stability of Signal Detection.

Abstract

One of the basic problems in statistical communication theory is that of detecting, at the end of a communication channel, a signal imbedded in noise. The Gaussian model is a model for which the noise as well as the received signal are Gaussian processes with equivalent laws, so that the resulting detection problem is nonsingular. Unfortunately most solutions to problems involving signals in Gaussian noise are based on a knowledge of the auto-correction function or spectrum (if the noise is stationary). This document studies the probabilties of false alarm and false dismissal for sure signals embedded in additive noise. The noise is contaminated Gaussian, and the framework is such that continuous-time problems can be studied.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA138525

Entities

People

  • A. F. Gualtierotti

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • C4I
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Convergence
  • Covariance
  • Detection
  • False Alarms
  • Gaussian Noise
  • Hilbert Space
  • North Carolina
  • Numbers
  • Probability
  • Random Variables
  • Signal Detection
  • Square Roots
  • Stationary Processes
  • Statistics
  • Stochastic Processes
  • Warning Systems
  • Weak Convergence

Fields of Study

  • Engineering

Readers

  • Acoustics.
  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.