方法证据记录
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Dynamic Time Warping Distance
分类方法记录 · mcdm / decision-making
- 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
- Salvador, S., & Chan, P. (2007). FastDTW: Toward accurate dynamic time warping in linear time and space. KDD Explorations, 5(1), 70-86. · URL
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