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.
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Mumtaz, W., Subhani, A.R. (2012). Adaptive Noise Cancellation: A Comparison of Adaptive Filtering Algorithms Aiming Fetal ECG Extraction. In: Qian, Z., Cao, L., Su, W., Wang, T., Yang, H. (eds) Recent Advances in Computer Science and Information Engineering. Lecture Notes in Electrical Engineering, vol 128. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25792-6_97
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DOI: https://doi.org/10.1007/978-3-642-25792-6_97
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