Denoising of Biological Signals Using Different Wavelet Based Methods and Their Comparison

Denoising of EEG signals using different wavelet shrinkage methods is proposed in this study. We applied these methods to denoise EEG signal contaminated with additive Gaussian noise. In these methods Visu Shrink, minimizing the False Discovery Rate (minFDR), Top, Hypothesis Testing thresholding rules and Hard, Soft thresholding filters are considered. The performances of these methods are evaluated and the results are compared using Mean Square Error (MSE) and Signal to Noise Ratio (SNR). Experiments revealed that minFDR and Hypothesis Testing rules with Hard thresholding filter and Top rule with Soft thresholding filter perform superior to other combinations of thresholding rules and filters.