Processing of time-dependent data is one of the basic disciplines of general data analysis. This electronic textbook provides an overview of fundamental algorithms used in time series processing. It is divided into two parts. The first part (Chapters 1 to 4) describes the basic types of experimental time series and their properties, elementary mathematical operations used in time series processing and, finally, frequency-based Fourier analysis, both of time-continuous functions and of discrete time series. The second part (Chapters 5 to 10) deals with linear models of time series. It introduces the basic methods for the description of their characteristics, deals with their computational structures and their frequency responses. Finally, it describes various algorithms for the separation of elementary components of time series, particularly for the separation of a time series drift.
