Smoothing filters are essential tools in Electroencephalography (EEG) signal processing, used to reduce noise and highlight underlying patterns. These filters work by averaging or weighting neighboring data points to create a smoother representation of the signal. The average filter computes the mean of nearby samples, reducing high-frequency noise. In this chapter we consider popular algorithms for smoothing filters.