The Fuzzy Relevance Vector Machine and its application to noise reduction in ECG signal

• Autorzy: Momot A. , Momot M. , Łęski J.
• Języki publikacji: EN

Abstrakty

EN

The paper presents new method called the Fuzzy Relevance Vector Machine (FRVM), a modification of the relevance vector machine, introduced by M. Tipping, applied to learning Takagi-Sugeno-Kang (TSK) fuzzy system. Moreover it describes application of the FRVM to noise reduction in ECG signal. The results of the process are compared to those obtained using both Least Squares method for learning output functions in TSK rules and commonly used method using a low-pass moving average filter.

Słowa kluczowe

EN

fuzzy systems; Bayesian inference; ECG signal

PL

systemy rozmyte; wnioskowanie bayesowskie; sygnał EKG

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2005
• Tom: Vol. 9
• Strony: 99--105
• Opis fizyczny: Bibliogr. 15 poz., rys., tab.

Twórcy

autor

Momot A.

• Silesian University of Technology, Institute of Computer Science, 16 Akademicka St., 44-101 Gliwice, Poland

autor

Momot M.

• Institute of Medical Technology and Equipment, 118 Roosevelt St., 41-800 Zabrze, Poland

autor

Łęski J.

• Institute of Medical Technology and Equipment, 118 Roosevelt St., 41-800 Zabrze, Poland
• Silesian University of Technology, Institute of Electronics, 16 Akademicka St., 44-101 Gliwice, Poland

Bibliografia

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