In this thesis an overview is given of basic terms and methods regarding digital signal processing. The term signal is defined and various categories of signals are mentioned. Representation of signals in the digital domain is in large part possible due to deficiencies in human hearing system. Hence, human perception of three major psychoacustic signal properties: pitch, loudness and color, is described, along with their connection to the physical signal properties frequency and intensity. In digital systems one can only work with a finite amount of data and storage. That is why it is necessary to modify time continuous analog signals to a finite amount of data which represents the original signal as closely as possible. Main methods in converting time continuous analog signals to discrete time digital signals: sampling, quantization and coding, are described, along with some of the byproducts, like aliasing. The description of a pulse-code modulation architecture is given. Basic terminology and concepts regarding filters in frequency and time domain are stated. Moving average filter is described and Python implementation of a said filter is given.