A normalized data-reusing least-mean-square algorithm of noise cancellation for magnetocardiography

Abstract

An adaptive filter based on Data-Reusing Least-Mean-Square algorithm has been proposed and applied in magnetocardiography (MCG) to suppress ambient noise. Numerical simulation studies indicate that the adaptive filter is a powerful noise suppresser for correlated interferences, especially for those with amplitude changing and time delay. Also the filter has a wide frequency bandwidth. With this filter, the signal-to-noise ratio of an MCG is improved to the intrinsic noise level. The periodic average method for further improvement of the noise level in MCG is also discussed.