The amount of time series data generated is increasing due to the integration of sensor technologies with everyday applications, such as gesture recognition, energy optimization, health care, video surveillance. The use of multiple sensors simultaneously
for capturing different aspects of the real world attributes has also led to an increase in dimensionality from uni-variate to multi-variate time series. This has facilitated richer data representation but also has necessitated algorithms determining similarity between two multi-variate time series for search and analysis.
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- Partial requirement for: M.S., Arizona State University, 2015Note typethesis
- Includes bibliographical references (pages 74-78)Note typebibliography
- Field of study: Computer science