Extraction of fetal electrocardiogram using recursive least squares and normalized least mean squares algorithms - Shi-jin Liu; Da-li Liu; Jing-quan Zhang; Yan-jun Zeng (2011 3rd International Conference on Advanced Computer Control, 2011)
This paper addresses the problem of fetal electrocardiogram (FECG) extraction using recursive least squares (RLS) and normalized least mean squares (NLMS) adaptive algorithms based adaptive noise canceling (ANC) approach. The simulation results are compared with the classical adaptive filters, such as RLS, NLMS and LMS algorithms, for eliminating the maternal electrocardiogram (MECG) and hence to extract the FECG. The comparative study has been carried out to show that the performance and accuracy of the recursive least squares adaptive noise cancelling(RLS-ANC) approach is more effective than the normalized least mean squares (NLMS) algorithm in an adaptive manner, and it is found to converge faster than NLMS algorithm in ANC.