Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package [PDF]
Journal of Statistical Software, 2009 Dynamic time warping is a popular technique for comparing time series, providing both a distance measure that is insensitive to local compression and stretches and the warping which optimally deforms one of the two input series onto the other.
Toni Giorgino
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DYNAMIC TIME WARPING FOR CROPS MAPPING [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Dynamic Time Warping (DTW) has been successfully used for crops mapping due to its capability to achieve good classification results when a reduced number of training samples and irregular satellite image time series is available.
M. Belgiu +3 more
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Similarity join over multiple time series under Dynamic Time Warping
CTU Journal of Innovation and Sustainable Development, 2023 Similarity join over multiple time series is an interesting task of data mining. This task aims at identifying couples of similar subsequences from multiple time series and the two subsequences might have any length and be at any position in the time ...
Bui Cong Giao
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Efficient Time Series Clustering by Minimizing Dynamic Time Warping Utilization
IEEE Access, 2021 Dynamic Time Warping (DTW) is a widely used distance measurement in time series clustering. DTW distance is invariant to time series phase perturbations but has a quadratic complexity.
Borui Cai +4 more
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Using Multi-Dimensional Dynamic Time Warping to Identify Time-Varying Lead-Lag Relationships
Sensors, 2022 This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify varying lead-lag relationships between two different time series.
Johannes Stübinger, Dominik Walter
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Improved LDTW Algorithm Based on the Alternating Matrix and the Evolutionary Chain Tree
Sensors, 2022 Dynamic time warping under limited warping path length (LDTW) is a state-of-the-art time series similarity evaluation method. However, it suffers from high space-time complexity, which makes some large-scale series evaluations impossible.
Zheng Zou +3 more
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Voice Transformation Using Two-Level Dynamic Warping and Neural Networks
Signals, 2021 Voice transformation, for example, from a male speaker to a female speaker, is achieved here using a two-level dynamic warping algorithm in conjunction with an artificial neural network.
Al-Waled Al-Dulaimi +2 more
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Seeded Classification of Satellite Image Time Series with Lower-Bounded Dynamic Time Warping
Remote Sensing, 2022 Satellite Image Time Series (SITS) record the continuous temporal behavior of land cover types and thus provide a new perspective for finer-grained land cover classification compared with the usual spectral and spatial information contained in a static ...
Zheng Zhang +5 more
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Malaysia PM10 Air Quality Time Series Clustering Based on Dynamic Time Warping
Atmosphere, 2022 Air quality monitoring is important in the management of the environment and pollution. In this study, time series of PM10 from air quality monitoring stations in Malaysia were clustered based on similarity in terms of time series patterns.
Fatin Nur Afiqah Suris +4 more
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Similarity Measure Based on Incremental Warping Window for Time Series Data Mining
IEEE Access, 2019 A similarity measure is one of the most important tasks in the fields of time series data mining. Its quality often affects the efficiency and effectiveness of the related algorithms that need to measure the similarity between two time series in advance.
Hailin Li, Cheng Wang
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