A new method of piecewise linear approximation of non-stationary time series

Abstract

Recently, in data science one of the most important issues has been discovering actionable information, interpretable patterns and relationships
in large volumes of data. This process is called data mining and is commonly being used in science, engineering, business and security.
One of the main methods of data mining is similarity search of time series. The approach that is discussed in this article is based on Piecewise
Linear Representation of time series that imply two steps of measuring time series similarity. A new method of piecewise linear approximation
of non-stationary time series is developed.