• DocumentCode
    1022126
  • Title

    An application of the generalized Neyman-Pearson fuzzy test to stochastic-signal detection

  • Author

    Son, Jae Cheol ; Song, Iickho ; Kim, Sun Yong ; Park, Seong III

  • Author_Institution
    Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Daejon, South Korea
  • Volume
    23
  • Issue
    5
  • fYear
    1993
  • Firstpage
    1474
  • Lastpage
    1481
  • Abstract
    In the article an application of the fuzzy testing of hypothesis to the stochastic-signal detection problem is considered when the signal-to-noise ratio approaches zero. We first obtain the general relationship between the test statistic of the locally optimum fuzzy detector and that of the locally optimum detector. Based on this result, the test statistic and structures of the locally optimum fuzzy detector for stochastic signals are obtained. Several aspects of the locally optimum fuzzy nonlinearity for stochastic signals are also described. Finally, performance characteristics of the locally optimum fuzzy detector are briefly discussed
  • Keywords
    fuzzy set theory; signal detection; statistical analysis; generalized Neyman-Pearson fuzzy test; locally optimum fuzzy detector; locally optimum fuzzy nonlinearity; signal-to-noise ratio; stochastic-signal detection; test statistic; Automatic control; Detectors; Motion control; Path planning; Quantization; Robotics and automation; Signal detection; Statistical analysis; Stochastic processes; Testing;
  • fLanguage
    English
  • Journal_Title
    Systems, Man and Cybernetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9472
  • Type

    jour

  • DOI
    10.1109/21.260679
  • Filename
    260679