SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS.

Published

Journal Article

A numerical method for computing likelihood ratios and corresponding processor performance is developed. When forming the likelihood ratio of the received data, the densities from which the data are generated are assumed to be discrete and finite. This modification results in a relatively simple set of computations which may be applied to a wide range of problem situations. Several examples of detection performance in non-Gaussian environments are presented including ROC curves and processor nonlinearities.

Duke Authors

Cited Authors

  • Zeferjahn, K; Nolte, LW

Published Date

  • December 1, 1984

Start / End Page

  • 315 - 317

Citation Source

  • Scopus