Quantifying morphology changes in time series data with skew

Quantifying morphology changes in time series data with skew

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), a...

Full description

Bibliographic Details
Main Authors: Sung, Phil (Contributor), Syed, Zeeshan (Contributor), Guttag, John V. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers, 2011-04-06T20:47:21Z.
Subjects:
Article
Online Access:Get fulltext

Internet

Get fulltext

Similar Items