ON THE CONVERGENCE OF ERROR PROBABILITIES FOR SIGNAL DETECTION,

Abstract

In Kelley, Reed, and Root (1960), it was shown that if the log of the likelihood ratio for detecting a signal in stationary Gaussian noise is phi sub T when the data is z(t), t epsilon (-T,T) and phi when the data is z(t), t epsilon (minus infinity, infinity), then Var phi sub T increases monotonically to Var(phi) as T approaches infinity. Recently, this result was extended to vector-valued stationary noise processes by Salehi (1968). In each case the purpose was to show that the probability of error for t epsilon (-T,T) converges to the probability of error for t epsilon (minus infinity, infinity). The purpose of this paper is to show that both of the results above are but special cases of a more fundamental result to be given here. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1969
Accession Number
AD0689153

Entities

People

  • Percy A. Pierre

Organizations

  • RAND Corporation

Tags

DTIC Thesaurus Topics

  • Convergence
  • Gaussian Noise
  • Noise
  • Probability
  • Signal Detection
  • Stationary

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Analytical Mechanics