LMS Adaptive Noise Canceler Design for ECG Signal Filtering
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Resource Overview
Design of an LMS adaptive noise canceler for fetal ECG signal processing, where fetal signals contain maternal signal noise. The implementation uses adaptive algorithms to cancel maternal signals, thereby extracting clean fetal ECG signals through gradient-based weight optimization.
Detailed Documentation
The LMS adaptive noise canceler designed for ECG signal filtering effectively removes maternal signal noise from fetal signals. By employing adaptive algorithms with gradient descent optimization, this system continuously adjusts filter coefficients to minimize interference, resulting in purer fetal ECG signals. This design enhances signal quality and accuracy, providing physicians and researchers with more detailed and reliable data to advance developments in related fields. Key implementation involves real-time coefficient updates using the Widrow-Hoff LMS algorithm via the formula: w(n+1) = w(n) + μ * e(n) * x(n), where μ controls convergence rate, e(n) represents error, and x(n) denotes the reference input.
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