Adaptive Noise Cancellation: A Comparison of Adaptive Filtering Algorithms Aiming Fetal ECG Extraction

Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 128)

Abstract

The paper focuses on the performance evaluation of adaptive noise cancellation algorithms in the context of electrocardiogram (ECG) signals. Four different algorithms i.e. Adaptive Filtering with Averaging (AFA), Least Mean Square (LMS), Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) are chosen for evaluation purposes. The performance metrics chosen for this purpose are signal to noise ratio (SNR), processing time and mean square error (MSE). Experimental results are presented which explains the simulation results showing the best performances among the above mentioned algorithms.

Keywords

Little Mean Square Independent Component Analysis Blind Source Separation Recursive Least Square Little Mean Square Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan

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