Performance Evaluation of S-Golay and MA Filter on the Basis of White and Flicker Noise

EEG is one of the most effective diagnostic techniques to evaluate the electrical activity in brain. For that we use a variety of filters to reduce the artifacts existing in the EEG signal. The main objective of the paper is to compare the functioning of the two commonly used filters i.e. the moving average and S-Golay. This is done by creating a synthetic signal and then by adding white or flicker (pink) noise to it. The analysis is made on the basis of performance of filters on SNR of the final output while keeping the same number of reference points (frame length) and observing the distortion ratio. Furthermore the most important information of EEG signal lies in the peak of the signal so it becomes absolutely necessary to use a filter that not only filters out the noise better but simultaneously shows the ability to provide the least distortion from the original signal. The shape preserving characteristics of the filter are determined at different noise levels and peaks are detected.