Dynamic time warping (DTW) is a technique for aligning curves that considers two aspects of variations: horizontal and vertical, or domain and range.This alignment is an essential preliminary in many applications before classification or functional data analysis. A problem with DTW is that the algorithm may fail to find the natural alignment of two series since it is mostly influenced by salient features rather than by the overall shape of the sequences. In this paper, we firstdeepen the DTW algorithm, showing relationships and differences with the curve registration technique, and then we propose a modification of the algorithm that considers a smoothed version of the data
Master's thesis in Computer scienceDynamic Time Warping (DTW) is a well-known technique used to dete...
While there exist a plethora of classification algorithms for most data types, there is an increasin...
In this work we address the problem of comparing time series while taking into account both feature ...
Dynamic time warping is a popular technique for comparing time series, providing both a distance mea...
International audienceDynamic Time Warping (DTW) is probably the most popular distance measure for t...
Following our previous works where an improved dynamic time warping(DTW) algorithm has been proposed...
Dynamic Time Warping (DTW) is a time series distance measure that allows non-linear alignments betwe...
Dynamic time warping (DTW) is a popular time series distance measure that aligns the points in two s...
Dynamic time warping (DTW) is a distance measure to compare time series that exhibit similar pattern...
AbstractMeasuring the similarity or distance between two time series sequences is critical for the c...
Dynamic Time Warping (DTW) is a popular time series distance measure that aligns the points in two s...
Dynamic Time Warping is arguably the most popular similarity measure for time series, where we defin...
The Dynamic Time Warping (DTW) distance is a popular measure of similarity for a variety of sequence...
Master's thesis in Computer scienceDynamic Time Warping (DTW) is a well-known technique used to dete...
While there exist a plethora of classification algorithms for most data types, there is an increasin...
In this work we address the problem of comparing time series while taking into account both feature ...
Dynamic time warping is a popular technique for comparing time series, providing both a distance mea...
International audienceDynamic Time Warping (DTW) is probably the most popular distance measure for t...
Following our previous works where an improved dynamic time warping(DTW) algorithm has been proposed...
Dynamic Time Warping (DTW) is a time series distance measure that allows non-linear alignments betwe...
Dynamic time warping (DTW) is a popular time series distance measure that aligns the points in two s...
Dynamic time warping (DTW) is a distance measure to compare time series that exhibit similar pattern...
AbstractMeasuring the similarity or distance between two time series sequences is critical for the c...
Dynamic Time Warping (DTW) is a popular time series distance measure that aligns the points in two s...
Dynamic Time Warping is arguably the most popular similarity measure for time series, where we defin...
The Dynamic Time Warping (DTW) distance is a popular measure of similarity for a variety of sequence...
Master's thesis in Computer scienceDynamic Time Warping (DTW) is a well-known technique used to dete...
While there exist a plethora of classification algorithms for most data types, there is an increasin...
In this work we address the problem of comparing time series while taking into account both feature ...