DocumentCode :
2617082
Title :
Implementing the fuzzy quadratic classifier
Author :
Kersten, Paul R.
Author_Institution :
Weapons Div., Naval Air Warfare Center, China Lake, CA, USA
fYear :
1997
fDate :
21-24 Sep 1997
Firstpage :
205
Lastpage :
210
Abstract :
The fuzzy quadratic classifier (FQC) extends the quadratic classifier to accommodate a sequence of fuzzy numbers as data. The fuzzy data induces a fuzzy quadratic discriminant (QD) that is then compared to other fuzzy discriminants to produce a decision. To generate the fuzzy data, conversion of batches of data vectors, or signals, into sequences of fuzzy signal vectors is developed base on fuzzy order statistics. In data rich environment, this conversion both condenses and refines the data stream. An efficient implementation of the FQC is presented based upon a diagonal form of the quadratic classifier and robust estimation of the parameters. A two class problem illustrates the procedure
Keywords :
decision theory; estimation theory; fuzzy set theory; parameter estimation; pattern classification; data vectors; decision; diagonal form; fuzzy discriminants; fuzzy numbers; fuzzy quadratic classifier; fuzzy quadratic discriminant; quadratic classifier; robust estimation; Additive noise; Gaussian distribution; Gaussian noise; Lakes; Noise robustness; Parameter estimation; Signal generators; Statistics; Target recognition; Weapons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
Conference_Location :
Syracuse, NY
Print_ISBN :
0-7803-4078-7
Type :
conf
DOI :
10.1109/NAFIPS.1997.624038
Filename :
624038
Link To Document :
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