Title :
A fuzzy set theoretic approach to signal detection
Author :
Son, Jae Cheol ; Song, Iickho ; Kim, Sangyoub
Author_Institution :
Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
Abstract :
A reformulation of the generalized Neyman-Pearson lemma is attempted using the fuzzy set theory. Based on the result, a locally optimum (or locally most powerful) fuzzy test is defined and the locally optimum fuzzy test function is derived. As a practical application of the locally optimum fuzzy test, detection of weak deterministic signals corrupted by purely additive noise, which is an important problem in statistical signal processing, is considered. Comparisons between the locally optimum and the locally optimum fuzzy tests are also made
Keywords :
fuzzy set theory; noise; signal detection; signal processing; additive noise; fuzzy set theory; generalized Neyman-Pearson lemma; locally optimum fuzzy test function; locally optimum test; signal detection; statistical signal processing; weak deterministic signals; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Minimax techniques; Probability distribution; Signal detection; Signal processing; Statistical analysis; Testing;
Conference_Titel :
Communications, Computers and Signal Processing, 1991., IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-87942-638-1
DOI :
10.1109/PACRIM.1991.160703
