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
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;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on