Review and comparison of smoothing algorithms for one-dimensional data noise reduction

The paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The parameters of denoising filters were selected with respect to the mean-square error between the computed linear regression and the noisy signal. Finally, we have compared mean, median, Savitzky-Golay, Kalman and Gaussian filter algorithms for the data from the digital sensor. The figure of merit was also the algorithm execution time.