RBF Neural Networks-Based Adaptive Noise Filtering from the ECG Signal

방사기저함수 신경망을 기반한 ECG신호의 적응펄터링

The ECG signal is very important information for diagnosis of patient and a cardiac disorder. It is hard to remove the noise because that is mixed with a lot of noise, and the error of the filtering will distort the ECG signal. The existing method for the filtering of the ECG signal has structure that has many steps for filtering, so that structure is complex and the processing speed is slow. For the improvement of that problem, we propose the method of filtering that has simple structure using the RBF neural networks and have good results.