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      Noise enhanced detection in restricted Neyman-Pearson framework

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      Author(s)
      Bayram, S.
      Gültekin, San
      Gezici, Sinan
      Date
      2012-06
      Source Title
      13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE 2012
      Publisher
      IEEE
      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.
      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
      Permalink
      http://hdl.handle.net/11693/28144
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SPAWC.2012.6292975
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      • Department of Computer Engineering 1435
      • Department of Electrical and Electronics Engineering 3702
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