NLMS algorithm with decreasing step size for adaptive IIR filters
Signal Processing
Subband-adaptive shrinkage for denoising of ECG signals
EURASIP Journal on Applied Signal Processing
Adaptive Filters
New gradient-based variable step size LMS algorithms
EURASIP Journal on Advances in Signal Processing
Advanced Biosignal Processing
A variable step-size matrix normalized subband adaptive filter
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Signal Processing
A new class of gradient adaptive step-size LMS algorithms
IEEE Transactions on Signal Processing
A robust variable step-size LMS-type algorithm: analysis andsimulations
IEEE Transactions on Signal Processing
Steady-State Performance Analysis of a Variable Tap-Length LMS Algorithm
IEEE Transactions on Signal Processing
A New Robust Variable Step-Size NLMS Algorithm
IEEE Transactions on Signal Processing
A Non-Linear Approach to ECG Signal Processing using Morphological Filters
International Journal of Measurement Technologies and Instrumentation Engineering
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In this paper several variable step size adaptive filter structures for extracting high resolution electrocardiographic ECG signals are presented which estimates the deterministic components of the ECG signal and removes the artifacts. The noise canceller minimizes the mean square error MSE between the input noisy ECG signal and noise reference. Different noise canceller structures are proposed to remove diverse forms of artifacts: power line interference, baseline wander, muscle artifacts and electrode motion artifacts. The proposed implementation is suitable real time applications, where large signal to noise ratios with fast convergence are required. Simulation studies shows that the proposed realization gives better performance compared to existing realizations in terms of signal to noise ratio, convergence rate and MSE.