Inaccuracies of shape averaging method using dynamic time warping for time series data

Abstract

Shape averaging or signal averaging of time series data is one of the prevalent subroutines in data mining tasks, where Dynamic Time Warping distance measure (DTW) is known to work exceptionally well with these time series data, and has long been demonstrated in various data mining tasks involving shape similarity among various domains. Therefore, DTW has been used to find die average shape of two time series according to the optimal mapping between them. Several methods have been proposed, some of which require the number of time series being averaged to be a power of two. In this work, we will demonstrate that these proposed methods cannot produce the real average of the time series. We conclude with a suggestion of a method to potentially find the shape-based time series average. © Springer-Verlag Berlin Heidelberg 2007.