Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series
share
Dynamic Time Warping (DTW) is a well-known similarity measure for time series. The standard dynamic programming approach to compute the dtw-distance of two length-n time series, however, requires O(n^2) time, which is often too slow in applications. Therefore, many heuristics have been proposed to speed up the dtw computation. These are often based on approximating or bounding the true dtw-distance or considering special inputs (e.g. binary or piecewise constant time series). In this paper, we present a fast and exact algorithm to compute the dtw-distance of two run-length encoded time series. This might be used for fast and accurate indexing and classification of time series in combination with preprocessing techniques such as piecewise aggregate approximation (PAA).
READ FULL TEXT
