Noise enhanced detection in restricted Neyman-Pearson framework

Date
2012-06
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Source Title
13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE 2012
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Publisher
IEEE
Volume
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Pages
575 - 579
Language
English
Type
Conference Paper
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Abstract

Noise enhanced detection is studied for binary composite hypothesis-testing problems in the presence of prior information uncertainty. The restricted Neyman-Pearson (NP) framework is considered, and a formulation is obtained for the optimal additive noise that maximizes the average detection probability under constraints on worst-case detection and false-alarm probabilities. In addition, sufficient conditions are provided to specify when the use of additive noise can or cannot improve performance of a given detector according to the restricted NP criterion. A numerical example is presented to illustrate the improvements obtained via additive noise. © 2012 IEEE.

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Keywords
Binary hypothesis-testing, Neyman-Pearson, Noise enhanced detection, Binary composites, Detection probabilities, Numerical example, Prior information, Spectrum sensing, Sufficient conditions, Additive noise, Signal processing, Wireless telecommunication systems, Detectors
Citation
Published Version (Please cite this version)