TY - JOUR
T1 - Detecting fixed amplitude signals in a fuzzy Gaussian environment
AU - Minett, J. W.
AU - Leung, S. W.
AU - Wong, P. W.
PY - 1999
Y1 - 1999
N2 - 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.
AB - 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.
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UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-16744364489&origin=recordpage
U2 - 10.1109/ICSMC.1999.814141
DO - 10.1109/ICSMC.1999.814141
M3 - RGC 21 - Publication in refereed journal
SN - 0884-3627
VL - 1
JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
T2 - 1999 IEEE International Conference on Systems, Man, and Cybernetics
Y2 - 12 October 1999 through 15 October 1999
ER -