Hyper-trim shrinkage for denoising of ECG signal
Digital Signal Processing
De-noising by soft-thresholding
IEEE Transactions on Information Theory
Class-Adaptive denoising for EEG data classification
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers
International Journal of Measurement Technologies and Instrumentation Engineering
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This paper describes subband dependent adaptive shrinkage function that generalizes hard and soft shrinkages proposed by Donoho and Johnstone (1994). The proposed new class of shrinkage function has continuous derivative, which has been simulated and tested with normal and abnormal ECG signals with added standard Gaussian noise using MATLAB. The recovered signal is visually pleasant compared with other existing shrinkage functions. The implication of the proposed shrinkage function in denoising and data compression is discussed.