Adaptive signal processing
Computers and Biomedical Research
Wavelets and subband coding
A New Adaptive Algorithm For Eliminating Sinusoidal Interferences
MWSCAS '98 Proceedings of the 1998 Midwest Symposium on Systems and Circuits
Hyper-trim shrinkage for denoising of ECG signal
Digital Signal Processing
IEEE Transactions on Signal Processing
An adaptive notch filter with improved tracking properties
IEEE Transactions on Signal Processing
Single section least squares adaptive notch filter
IEEE Transactions on Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
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This paper proposes a new technique to eliminate the power line frequency from the electrocardiogram (ECG) signal. Donoho and Johnstone (1994) were the first to formalize the wavelet coefficient threshold based shrinkage function for removal of additive noise from deterministic signals. The discrimination between signal and noise is achieved by choosing an orthogonal basis, which efficiently approximates the signal (with few nonzero coefficients). A signal enhancement can thus be obtained by discarding components below a predetermined threshold. In the proposed technique, the shrinkage function is incorporated at the vicinity of power line frequency by selecting the proper subband level. The proposed technique is found to be simple to implement in real-time applications. The computational complexity of the proposed technique is very less compared to any other adaptive techniques. The proposed technique is simulated and tested in MATLAB. The recovered signal is visually pleasant compared with other conventional method.