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|a Sung, Phil
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Guttag, John V.
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|a Sung, Phil
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|a Syed, Zeeshan
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|a Guttag, John V.
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|a Syed, Zeeshan
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|a Guttag, John V.
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|a Quantifying morphology changes in time series data with skew
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|b Institute of Electrical and Electronics Engineers,
|c 2011-04-06T20:47:21Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/62155
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|a This paper examines strategies to quantify differences in the morphology of time series while accounting for time skew in the observed data. We adapt four measures originally designed for signal shape comparison: Dynamic Time-Warping (DTW), Earth Mover's Distance (EMD), Frochet Distance (FD), and Hausdorff Distance (HD). These morphology difference metrics on time series are compared in discriminative power and noise resistance on ECG signals as well as on a synthetic dataset. We use data from our experiments to shed light on the relative strengths of the methods.
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|a en_US
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|a Article
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|t ICASSP (IEEE International Conference on Acoustics, Speech and Signal Processing)
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