Adaptive non-linear filtering of ECG signals: dynamic neural network approach

This paper describes some aspects of using dynamic neural networks in predictive-type ECG filtering in comparison with adaptive linear filters. Two new algorithms are introduced and their performance is compared with normal and temporal backpropagation algorithms in terms of both the signal-to-noise ratio and the signal quality. The results indicate that using variant step size in learning algorithms improves the signal quality