Journal of Computer Applications ›› 2023, Vol. 43 ›› Issue (6): 1855-1860.DOI: 10.11772/j.issn.1001-9081.2022060885
• Data science and technology • Previous Articles Next Articles
Received:
2022-06-20
Revised:
2022-08-04
Accepted:
2022-08-11
Online:
2022-10-11
Published:
2023-06-10
Contact:
Chengyun SONG
About author:
QIU Lianpeng, born in 1995, M. S. candidate. Her research interests include big data, intelligent signal processing.
Supported by:
通讯作者:
宋承云
作者简介:
邱莲鹏(1995—),女,甘肃定西人,硕士研究生,主要研究方向:大数据、智能信号处理CLC Number:
Lianpeng QIU, Chengyun SONG. Noise robust dynamic time warping algorithm[J]. Journal of Computer Applications, 2023, 43(6): 1855-1860.
邱莲鹏, 宋承云. 噪声鲁棒的动态时间规整算法[J]. 《计算机应用》唯一官方网站, 2023, 43(6): 1855-1860.
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URL: http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2022060885
数据集 | 类别数 | 训练集数 | 测试集数 | 序列长度 |
---|---|---|---|---|
BeetleFly | 2 | 20 | 20 | 512 |
BirdChicken | 2 | 20 | 20 | 512 |
DistalPhalanxTW | 6 | 139 | 400 | 80 |
Fish | 7 | 175 | 175 | 463 |
Gun-Point | 2 | 50 | 150 | 150 |
Symbols | 6 | 25 | 995 | 398 |
ToeSegmentation1 | 2 | 40 | 228 | 277 |
ToeSegmentation2 | 2 | 36 | 130 | 343 |
Tab. 1 Information of datasets
数据集 | 类别数 | 训练集数 | 测试集数 | 序列长度 |
---|---|---|---|---|
BeetleFly | 2 | 20 | 20 | 512 |
BirdChicken | 2 | 20 | 20 | 512 |
DistalPhalanxTW | 6 | 139 | 400 | 80 |
Fish | 7 | 175 | 175 | 463 |
Gun-Point | 2 | 50 | 150 | 150 |
Symbols | 6 | 25 | 995 | 398 |
ToeSegmentation1 | 2 | 40 | 228 | 277 |
ToeSegmentation2 | 2 | 36 | 130 | 343 |
数据集 | ED | DTW | Sakoe-Chiba窗口DTW | WDTW | NoiseDTW |
---|---|---|---|---|---|
BeetleFly | 0.700 | 0.700 | 0.700 | 0.800 | |
BirdChicken | 0.550 | 0.700 | 0.900 | ||
DistalPhalanxTW | 0.727 | 0.710 | 0.604 | 0.758 | |
Fish | 0.783 | 0.823 | 0.846 | 0.874 | |
Gun-Point | 0.907 | 0.980 | 0.980 | ||
Symbols | 0.900 | 0.938 | 0.960 | ||
ToeSegmentation1 | 0.680 | 0.772 | 0.750 | 0.829 | |
ToeSegmentation2 | 0.808 | 0.838 | 0.892 | 0.920 |
Tab. 2 Classification accuracy on 8 time series datasets
数据集 | ED | DTW | Sakoe-Chiba窗口DTW | WDTW | NoiseDTW |
---|---|---|---|---|---|
BeetleFly | 0.700 | 0.700 | 0.700 | 0.800 | |
BirdChicken | 0.550 | 0.700 | 0.900 | ||
DistalPhalanxTW | 0.727 | 0.710 | 0.604 | 0.758 | |
Fish | 0.783 | 0.823 | 0.846 | 0.874 | |
Gun-Point | 0.907 | 0.980 | 0.980 | ||
Symbols | 0.900 | 0.938 | 0.960 | ||
ToeSegmentation1 | 0.680 | 0.772 | 0.750 | 0.829 | |
ToeSegmentation2 | 0.808 | 0.838 | 0.892 | 0.920 |
数据集 | DTW/s | WDTW/s | NoiseDTW/s |
---|---|---|---|
BeetleFly | 5 | 58 | 43 |
BirdChicken | 4 | 60 | 42 |
DistalPhalanxTW | 14 | 159 | 184 |
Fish | 194 | 3 394 | 2 144 |
Gun-Point | 6 | 76 | 72 |
Symbols | 102 | 1 980 | 1 016 |
ToeSegmentation1 | 17 | 326 | 225 |
ToeSegmentation2 | 12 | 266 | 162 |
Tab. 3 Comparison of time overhead of three algorithms
数据集 | DTW/s | WDTW/s | NoiseDTW/s |
---|---|---|---|
BeetleFly | 5 | 58 | 43 |
BirdChicken | 4 | 60 | 42 |
DistalPhalanxTW | 14 | 159 | 184 |
Fish | 194 | 3 394 | 2 144 |
Gun-Point | 6 | 76 | 72 |
Symbols | 102 | 1 980 | 1 016 |
ToeSegmentation1 | 17 | 326 | 225 |
ToeSegmentation2 | 12 | 266 | 162 |
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