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Communication Dans Un Congrès Année : 2011

Constrained epsilon-equalizer test for multiple hypothesis testing

Résumé

A constrained epsilon-equalizer test is proposed to detect and classify non-orthogonal vectors in Gaussian noise. The classification error probabilities of this test are equalized up to a negligible difference, subject to a constraint on the false alarm probability. It has a small loss of optimality with respect to the purely theoretical and incalculable constrained equalizer test provided that the norms of vectors to classify are sufficiently large. A numerical example confirms the theoretical findings.
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Dates et versions

hal-00923526 , version 1 (03-01-2014)

Identifiants

  • HAL Id : hal-00923526 , version 1

Citer

Lionel Fillatre. Constrained epsilon-equalizer test for multiple hypothesis testing. IEEE International Symposium on Information Theory Proceedings (ISIT), Jul 2011, St. Petersburg, Russia. pp.2994-2998. ⟨hal-00923526⟩
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