THE FUZZY RELEVANCE VECTOR MACHINE AND ITS APPLICATION TO NOISE REDUCTION IN ECG SIGNAL
Alina Momot, M. Momot, Jacek M. Łęski · Journal of Medical Informatics & Technologies · 2005
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.