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Questions tagged [dynamic-time-warping]

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How to do phoneme segmentation using dynamic time warping?

Background Information: Dynamic Time Warping (DTW): In time series analysis, dynamic time warping (DTW) is one of the algorithms for measuring similarity between two temporal sequences, which may vary in speed. (Source: Wikipedia) Phoneme…
Sam Kagawa
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Signal correlation - matching specific points

Question: What are some recommended techniques for matching specific patterns in data sets? Background I have several thousand sites for which I have collected time series data. In the example image below we have increasing time in y-direction with…
user1563247
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Calculate the similarity between pairs of time series data

I have 5 pieces of time series data. It is the weekly sales of 5 different stores (A,B,C,D,E). There are no missing values. A quick visual inspection shows that these 5 pieces of time series data have similar trend & seasonality. I would like to…
DPatrick
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clustering time series with different sized time series

I have read this article on towardsdatascience and they teach how to cluster time series using the DTW distance and the TimeSeriesKMeans from the tslearn.clustering library. I also read the official documentation and I found a note. Notes If metric…
Román
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Perform DTW simultaneously on multiple trajectories

Good day, I have ~50 sample trajectories (timeseries) showing reactor temperature over time for a given process. In addition, I have a reference signal of the ideal trajectory for this process. I would like to synchronize all the sample trajectories…
SimpleJack
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In DTW, is the distance the sum of the shortest path's elements or the fathest element?

The title says it. In dynamic time warping, I keep hearing that the distance between two distances is the sum of the shortest path's elements. But I also see the distance as the element in the farthest corner? Could somebody please clear this…
memesanddeath
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Dynamic Time Warping with fast lookup?

My understanding of Dynamic Time Warping is that the algorithm always requires calculation with each comparison/training series and that there is no way to extract the "essence" from a given training series in the form of coefficients, which could…
SuperCodeBrah
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Determining clusters of time series

I have been given time series of N stock prices and time series of K sectoral indices. (Sectoral index is index made from all stocks belonging to that sector.) I have not been given names of any of those stocks or indices. I want to know which…
RajS
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Patterns extraction in time serie with DTW

I have a long time serie, let's say 1000 items. I want to find patterns in it of different lengths from 10 to 100 elements. To do this, I extract sliding windows of different lengths and calculate distance matrix between them using DTW. But it works…
AlexRonsky
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corresponding class labels of two unsupervised learning algorithms

I am working on a time series clustering problem. I made two models (hierarchical tree) with different pre-processing techniques using this class in package dtaidistance: clustering.LinkageTree(dtw.distance_matrix_fast, {}) I am now studying the…
Triki Sadok
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Comparing time series classification with Hidden Markov Model vs Dynamic Time Warping - which model should I use to generate data?

Copied from Cross Validated I am writing a thesis which compares two approaches to time series classification: Hidden Markov Models and Dynamic Time Warping combined with 1-NN. I'll apply both algorithms to some real dataset, but first it would be…
Brzoskwinia
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Dynamic Time Warping (DTW) for time series with different step sizes

Is it possible to use Dynamic Time Warping (DTW) algorithm as a method to find the similarity between two time-series data that have different step/measurement sizes? For example, one is measured every hour and the other is measured every day.
Adel
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Is it possible to reduce the time of computing DTW with dtw-python package by disabling computation of?

I am trying to classify some time series using dtw-python package which is a python version of R package implementing Dynamic Time Warping described in this nice paper. By default a call to dtw function returns DTW object containing the distance as…
Brzoskwinia
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how to perform clustering using dtw and some clustering method like kmeans

I have a timeseries(temperature of a sensor)and I want to apply an unsupervised clustering that. I've already done that using sklearn library and Kmeans. but the problem is that I don't know how to add DTW as a metric. I need to compare timeseries…
Soroosh Moghimi
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