Detecting fixed amplitude signals in a fuzzy Gaussian environment

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Original languageEnglish
Journal / PublicationProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1999


Title1999 IEEE International Conference on Systems, Man, and Cybernetics
Period12 - 15 October 1999


In practical signal detection scenarios, parameters of a random process are often uncertain. In this paper, we model such uncertainties as fuzzy parameters of a stationary random process. A fuzzy Neyman-Pearson hypothesis test concept which accepts any number of fuzzy parameters is presented. A suitable decision rule is developed by applying theory for ordering fuzzy numbers, and stated in terms of a fuzzy threshold. A defuzzifying threshold is then applied to produce a crisp decision rule. The concepts developed here are applied to Neyman-Pearson detection of a fuzzy fixed amplitude signal in Gaussian noise with fuzzy variance.