Dynamic time warping under subsequence

Shengchuan Han; Lisheng Zhang

doi:10.1117/12.2640305

1 August 2022 Dynamic time warping under subsequence

Shengchuan Han, Lisheng Zhang

Author Affiliations +

Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 122571X (2022) https://doi.org/10.1117/12.2640305
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China

Abstract

In the mining and analysis of time series data, the similarity measurement process of two time series is essential. The dynamic time warping algorithm DTW (Dynamic Time Warping) is a common algorithm for measuring the similarity of time series. Although DTW has obtained the global optimal solution, it may not be able to achieve local reasonable matching, and the measurement effect is limited. The shape dynamic time warping algorithm shapeDTW (Shape Dynamic Time Warping) enhances the measurement effect by considering point-wise local structure information. In order to continue to improve the measurement effect of the shapeDTW algorithm, this paper analyzes the definition and common methods of the shape descriptor of its algorithm. On the basis of extending the subsequences at each time point, the method of representing subsequences using shape descriptors is directly changed. The DTW value of the subsequence is calculated as the distance value of each time point in the cumulative cost matrix during the alignment of the entire original time series. This method is called subDTW (Subsequence Dynamic Time Warping). The subDTW algorithm enhances the measurement effect of the shapeDTW algorithm to a certain extent. Through the experimental research and analysis of the approximate window size of the segmentation aggregation on the training set, the subDTW algorithm based on the cumulative cost matrix pruning can keep the classification accuracy unchanged. A significant reduction in time overhead is achieved.

Citation Download Citation

Shengchuan Han and Lisheng Zhang "Dynamic time warping under subsequence", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 122571X (1 August 2022); https://doi.org/10.1117/12.2640305

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