Denoising of Biological Signals using Wavelets
T. Latha, Meenu Suresh · 2013
Methods based on thresholding of wavelet coefficients have been found to be popular in the estimation of biological signals from noisy environment. Hard and soft filters are most commonly used in these methods. In this paper a novel thresholding filter for wavelet shrinkage estimation of biological signals is proposed. The proposed novel filter is applied using Visu Shrink rule and top rule to denoise ECG signal contaminated with additive white Gaussian noise. The performance of the filter is compared with that of hard and soft filters. Mean Square Error (MSE) and Signal to Noise Ratio (SNR) are used as criteria for testing the performance of denoising. From the simulation results it is found that the novel filter performs better than soft filter with Visu rule and hard filter with top rule.