Results 231 to 240 of about 62,816 (280)
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Weighted Dynamic Time Warping for Time Series
International Journal of Bifurcation and Chaos, 2023Recurrence network is a typical time series analysis method. However, irregular sampling may overshadow the dynamic features characterized by traditional recurrence network method, which makes the method ineffective. This paper introduces dynamic time warping method to determine the distance between time series segments.
Guangyu Yang, Shuyan Xia
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DYNAMIC POSITIONAL WARPING: DYNAMIC TIME WARPING FOR ONLINE HANDWRITING
International Journal of Pattern Recognition and Artificial Intelligence, 2009This paper addresses the problem of dynamic time warping (DTW) causing unintended matching correspondences when it is employed for online two-dimensional (2D) handwriting signals, and proposes the concept of dynamic positional warping (DPW) in conjunction with DTW for online handwriting matching problems. The proposed DPW allows subsignal translations
WON-DU CHANG, JUNGPIL SHIN
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1984
Two programs are provided, one that generates Ipc and autocorrelation coefficients from the speech utterances and the other that, using dynamic programming, compares the test utterance with the reference utterances and finds the best match. The method used is Constrained Endpoint with 2-to-l range of slope.
Alan Bundy, Lincoln Wallen
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Two programs are provided, one that generates Ipc and autocorrelation coefficients from the speech utterances and the other that, using dynamic programming, compares the test utterance with the reference utterances and finds the best match. The method used is Constrained Endpoint with 2-to-l range of slope.
Alan Bundy, Lincoln Wallen
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Dynamic Time Warping Dissimilarity Matrices
IEEE Potentials, 2018The dynamic time-warping measure (DTW), also known as the DTW distance, is a widely used method that quantifies how dissimilar two time series are from each other. That quantification of the degree of dissimilarity is often motivated by tasks such as data exploration/visualization, clustering, and classification.
Ana Lorena Uribe-Hurtado +2 more
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Dynamic time warping in hardware
Proceedings of the 14th International Conference on Information Integration and Web-based Applications & Services, 2012The Dynamic Time Warping (DTW) algorithm is a commonly used algorithm in matching time sequence data in many applications that require some kind of similarity measure. Though effective, DTW is computationally intensive, and therefore is not suitable for real-time situations. In the past 30 years, there has been some research work on implementing DTW in
Kin Fun Li, James Shueyen Tai
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Dynamic frequency warping, the dual of dynamic time warping
The Journal of the Acoustical Society of America, 1987Comparison of two tokens of the same utterance is central to many automatic speech recognition systems. Matching is usually done in the frequency-time domain; token matching is effectively spectrogram matching. Dynamic time warping (DTW) overcomes, to some extent, the temporal variability of speech tokens; spectrograms are time-aligned by calculating ...
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Constrained Sparse Dynamic Time Warping
2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018Dynamic time warping (DTW) has been applied to a wide range of machine learning problems involving the comparison of time series. An important feature of such time series is that they can sometimes be sparse in the sense that the data takes zero value at many epochs.
Youngha Hwang, Saul B. Gelfand
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Dynamic time warping improves sewer flow monitoring
Water Research, 2013Successful management and control of wastewater and storm water systems requires accurate sewer flow measurements. Unfortunately, the harsh sewer environment and insufficient flow meter calibration often lead to inaccurate and biased data. In this paper, we improve sewer flow monitoring by creating redundant information on sewer velocity from natural ...
Dürrenmatt David J. +2 more
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Alignment Using Variable Penalty Dynamic Time Warping
Analytical Chemistry, 2009In this article we highlight a novel variation on dynamic time warping (DTW) for aligning chromatogram signals. We are interested in sets of signals that can be aligned well locally, but not globally, by shifting individual signals in time. This kind of alignment is often sufficient for aligning gas chromatography data.
Clifford, David +7 more
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Segmented Dynamic Time Warping
2019Initially used in speech recognition, the dynamic time warping algorithm (DTW) has regained popularity with the widespread use of time series data. While demonstrating good performance, this elastic measure has two significant drawbacks: high computational costs and the possibility of pathological warping paths.
Ruizhe Ma +3 more
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