Key result
The Proportionate LMS (PLMS) algorithm demonstrated improved noise cancellation performance for ECG signals compared to the conventional LMS algorithm across various noise types.
Why the study?
Does the Proportionate Linear Mean Square (PLMS) algorithm improve ECG noise removal compared to the conventional LMS algorithm?
Comparison
Proportionate linear Mean Square algorithm vs LMS
Authors
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ECG noise reduction approaches may aid interpretation; leaves open whether they improve diagnostic outcomes in practice.
Does the Proportionate Linear Mean Square (PLMS) algorithm improve ECG noise removal compared to the conventional LMS algorithm?
The proposed PLMS algorithm effectively reduces computational complexity and improves signal-to-noise ratio for ECG noise removal compared to conventional LMS.
Balasubramanian et al. (2022) studied ECG signal noise. Proportionate Linear Mean Square (PLMS) algorithm vs. Least Mean Square (LMS) algorithm was evaluated on Mean Square Error (MSE), Signal to Noise Ratio (SNR), and Root Mean Square Error (RMSE). The Proportionate LMS (PLMS) algorithm demonstrated improved noise cancellation performance for ECG signals compared to the conventional LMS algorithm across various noise types.
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