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Robust detection under Bhattacharyya metric

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2 Author(s)
Jana, Soumya ; Illinois Univ., Urbana, IL, USA ; Moulin, P.

In a variety of detection applications, robust techniques are used to cope with the uncertainty in the statistical model assumed for the data. Traditional methods using ε-contamination classes are often too restrictive. Other techniques require that the nominal densities be Gaussian. This paper proposes Bhattacharyya balls around arbitrary nominal distributions as a flexible yet realistic alternative in uncertainty modeling. We derive probability densities that are least discriminable in the Bhattacharyya metric.

Published in:

Statistical Signal Processing, 2003 IEEE Workshop on

Date of Conference:

28 Sept.-1 Oct. 2003

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