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SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS.

Publication ,  Journal Article
Zeferjahn, K; Nolte, LW
December 1, 1984

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 Scholars

Publication Date

December 1, 1984

Start / End Page

315 / 317
 

Citation

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Zeferjahn, K., & Nolte, L. W. (1984). SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS., 315–317.
Zeferjahn, K., and L. W. Nolte. “SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS.,” December 1, 1984, 315–17.
Zeferjahn K, Nolte LW. SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS. 1984 Dec 1;315–7.
Zeferjahn, K., and L. W. Nolte. SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS. Dec. 1984, pp. 315–17.
Zeferjahn K, Nolte LW. SIGNAL DETECTION IN NON-GAUSSIAN ENVIRONMENTS. 1984 Dec 1;315–317.

Publication Date

December 1, 1984

Start / End Page

315 / 317