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      Noise enhanced M-ary composite hypothesis-testing in the presence of partial prior information

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      Author
      Bayram, S.
      Gezici, Sinan
      Date
      2010-12-06
      Source Title
      IEEE Transactions on Signal Processing
      Print ISSN
      1053-587X
      Publisher
      IEEE
      Volume
      59
      Issue
      3
      Pages
      1292 - 1297
      Language
      English
      Type
      Article
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      Abstract
      In this correspondence, noise enhanced detection is studied for M-ary composite hypothesis-testing problems in the presence of partial prior information. Optimal additive noise is obtained according to two criteria, which assume a uniform distribution (Criterion 1) or the least-favorable distribution (Criterion 2) for the unknown priors. The statistical characterization of the optimal noise is obtained for each criterion. Specifically, it is shown that the optimal noise can be represented by a constant signal level or by a randomization of a finite number of signal levels according to Criterion 1 and Criterion 2, respectively. In addition, the cases of unknown parameter distributions under some composite hypotheses are considered, and upper bounds on the risks are obtained. Finally, a detection example is provided in order to investigate the theoretical results.
      Keywords
      Bayes risk
      Composite hypothesis-testing
      Detection
      Noise enhanced detection
      Permalink
      http://hdl.handle.net/11693/22013
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/TSP.2010.2097257
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      • Department of Electrical and Electronics Engineering 3524
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