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Method evidence record

Dynamic Time Warping

Dynamic Time Warping is a distance metric for comparing time series or sequential data that may vary in length or speed. Introduced by Hideki Sakoe and Seibi Chiba in 1978 for speech recognition, DTW measures the minimal cumulative distance needed to align two sequences using dynamic programming. Unlike fixed-distance metrics, DTW allows flexible time warping, making it ideal for sequences that are similar in shape but offset or scaled differently in time.

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Dynamic Time Warping Distance

Taxonomic method recordmcdmdecision-making

  1. Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43-49. · DOI 10.1109/TASSP.1978.1163055

  2. Salvador, S., & Chan, P. (2007). FastDTW: Toward accurate dynamic time warping in linear time and space. KDD Explorations, 5(1), 70-86. · URL

Open full method2 recorded citations, copied from the method source record.

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