Results 51 to 60 of about 10,387 (161)
On-Line Dynamic Time Warping for Streaming Time Series [PDF]
, 2017 Dynamic Time Warping is a well-known measure of dissimilarity between time series. Due to its flexibility to deal with non-linear distortions along the time axis, this measure has been widely utilized in machine learning models for this particular kind of data. Nowadays, the proliferation of streaming data sources has ignited the interest and attention
Izaskun Oregi +3 more
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IEEE AccessDynamic Time Warping (DTW) offers precise similarity measure but suffers from high computational cost. To address this issue, we propose an abstract-adaptive PAR-DTW, which computes DTW in a low-dimensional piecewise abstract representation (PAR) space ...
Qinglin Cai +3 more
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Object-Based Time-Constrained Dynamic Time Warping Classification of Crops Using Sentinel-2
Remote Sensing, 2019 The increasing volume of remote sensing data with improved spatial and temporal resolutions generates unique opportunities for monitoring and mapping of crops.
Ovidiu Csillik +3 more
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Derivative Dynamic Time Warping [PDF]
Proceedings of the 2001 SIAM International Conference on Data Mining, 2001 Eamonn J. Keogh, Michael J. Pazzani
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Feature trajectory dynamic time warping for clustering of speech segments
EURASIP Journal on Audio, Speech, and Music Processing, 2019 Dynamic time warping (DTW) can be used to compute the similarity between two sequences of generally differing length. We propose a modification to DTW that performs individual and independent pairwise alignment of feature trajectories.
Lerato Lerato, Thomas Niesler
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Flexible Dynamic Time Warping for Time Series Classification
Procedia Computer Science, 2015 AbstractMeasuring the similarity or distance between two time series sequences is critical for the classification of a set of time series sequences. Given two time series sequences, X and Y , the dynamic time warping (DTW) algorithm can calculate the distance between X and Y .
Che-Jui Hsu +3 more
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Sub-Sequence-Based Dynamic Time Warping
Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2019 In time series classification the most commonly used approach is k Nearest Neighbor classification, where k = 1, coupled with Dynamic Time Warping (DTW) similarity checking. A challenge is that the DTW process is computationally expensive. This paper presents a new approach for speeding-up the DTW process, Sub-Sequence-Based DTW, which offers the ...
Mohammed Alshehri +2 more
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Similarity Measurement of Biological Signals Using Dynamic Time Warping Algorithm
Proceedings of the International Conference on Applied Innovations in IT, 2016 The problem of similarity measurement of biological signals is considered on this article. The dynamic time warping algorithm is used as a possible solution. A short overview of this algorithm and its modifications are given.
Ivan Luzianin, Bernd Krause
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Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package
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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Improving the Robustness of DTW to Global Time Warping Conditions in Audio Synchronization
Applied SciencesDynamic time warping estimates the alignment between two sequences and is designed to handle a variable amount of time warping. In many contexts, it performs poorly when confronted with two sequences of different scale, in which the average slope of the ...
Jittisa Kraprayoon +2 more
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