کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6939722 | 1449973 | 2018 | 27 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Time-series averaging using constrained dynamic time warping with tolerance
ترجمه فارسی عنوان
میانگین زمان میانگین با استفاده از محدودیت پویا زمان انحراف با تحمل
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
چشم انداز کامپیوتر و تشخیص الگو
چکیده انگلیسی
In this paper, we propose an innovative averaging of a set of time-series based on the Dynamic Time Warping (DTW). The DTW is widely used in data mining since it provides not only a similarity measure, but also a temporal alignment of time-series. However, its use is often restricted to the case of a pair of signals. In this paper, we propose to extend its application to a set of signals by providing an average time-series that opens a wide range of applications in data mining process. Starting with an existing well-established method called DBA (for DTW Barycenter Averaging), this paper points out its limitations and suggests an alternative based on a Constrained Dynamic Time Warping. Secondly, an innovative tolerance is added to take into account the admissible variability around the average signal. This new modeling of time-series is evaluated on a classification task applied on several datasets and results show that it outperforms state of the art methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition - Volume 74, February 2018, Pages 77-89
Journal: Pattern Recognition - Volume 74, February 2018, Pages 77-89
نویسندگان
Marion Morel, Catherine Achard, Richard Kulpa, Séverine Dubuisson,