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Robust locally optimum detection of signals in dependent noise

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2 Author(s)
Gerlach, K. ; US Naval Res. Lab., Washington, DC, USA ; Sangston, K.J.

A robust locally optimum detector of a signal embedded in additive dependent nonGaussian noise is presented. The performance criterion is Bayes risk, the sample size is finite, and the uncertainty class of multivariate inputs is the ∈-contamination model. The locally optimum detector is shown to be a censored version of the nominal likelihood ratio

Published in:

Information Theory, IEEE Transactions on  (Volume:39 ,  Issue: 3 )

Date of Publication:

May 1993

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