A Study on Dynamic Time Warping

Dynamic time warping (DTW) is a pattern matching method that can reconcile similar characteristics of two trajectories based on dynamic programming, this technique has been used in the area of speech recognition successfully. This paper discusses the application of dynamic time warping (DTW) to the analysis and disposal unsynchronized trajectories of batch processes. In batch process, due to the presence of batch batch disturbances and existence of physical constraints, batch processes often are characterized by unsynchronized trajectories. To compare these batch histories and apply statistical analysis, one needs to reconcile the timing difference among these histories first. Dynamic time warping (DTW) has the ability to synchronize two trajectories by appropriately translating, expanding, and contracting localized segments within both trajectories to achieve a minimum distance between the trajectories and optimal path, then synchronize two trajectories.