In recent years, there are increasing numbers of applications that use multi-variate time series data where multiple uni-variate time series coexist. However, there is a lack of systematic of multi-variate time series. This thesis focuses on (a) defining a simplified inter-related multi-variate time series (IMTS) model and (b) developing robust multi-variate temporal (RMT) feature extraction algorithm that can be used for locating, filtering, and describing salient features in multi-variate time series data sets.
Download count: 0
- Partial requirement for: M.S., Arizona State University, 2013Note typethesis
- Includes bibliographical references (p. 65-69)Note typebibliography
- Field of study: Computer science