DocumentCode
3416501
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
fYear
1991
fDate
9-10 May 1991
Firstpage
150
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Computers and Signal Processing, 1991., IEEE Pacific Rim Conference on
Conference_Location
Victoria, BC
Print_ISBN
0-87942-638-1
Type
conf
DOI
10.1109/PACRIM.1991.160703
Filename
160703
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