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Optimization of Dynamic Time Warping Algorithm for Abnormal Signal Detection

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Abstract

This paper proposes an algorithm based on a combination of DTW lower bound functions and Sakoe–Chiba constraints to improve the time efficiency of DTW distance measurement, which suffers from a high computational complexity and low efficiency while ensuring measurement accuracy. First, the Sakoe–Chiba-DTW algorithm is used to optimize the template and threshold in the original sequence. Then, different combinations of lower bound functions are introduced to filter out sequences that do not meet the similarity requirements compared to the optimized threshold, reducing the number of DTW calculations to improve efficiency. The proposed algorithm is evaluated on 5 sets of self-built data samples for the detection and removal of interference signals caused by redundant objects. The results show that the algorithm achieves the same level of accuracy as traditional DTW algorithm, but saves up to 73880 s in detection time, greatly improving efficiency and having significant implications for data mining tasks.

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Funding

This research work was supported by the National Natural Science Foundation of China (51607059), the Natural Science Foundation of Heilongjiang Province (JJ2020LH1310, QC2017059), the Postdoctoral Fund of Heilongjiang Province (LBH-Z16169), the Basic Scientific Research Fund of Universities in Heilongjiang Province (2020-KYYWF-1006), and the Scientific and Technological Achievements Cultivation of Heilongjiang Provincial Department of Education (TSTAU-C2018016).

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Authors and Affiliations

  1. Electronic Engineering collage, Heilongjiang University, Harbin, 150001, China

    Yuru Teng, Guotao Wang, Cailing He, Yaoyang Wu & Chaoran Li

  2. Institute of Electrical and Electronic Reliability, Harbin Institute of Technology, Harbin, 150001, China

    Guotao Wang

Authors
  1. Yuru Teng
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  2. Guotao Wang
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  3. Cailing He
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  4. Yaoyang Wu
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  5. Chaoran Li
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Contributions

YR and GT conceived the proposed ideas. GT developed theories and methods. YR conducted experiments, and CL, YY, and CR verified the proposed method. All authors discussed the findings and contributed to the final manuscript.

Corresponding author

Correspondence to Guotao Wang.

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Teng, Y., Wang, G., He, C. et al. Optimization of Dynamic Time Warping Algorithm for Abnormal Signal Detection. Int J Data Sci Anal (2023). https://doi.org/10.1007/s41060-023-00446-0

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