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Article type: Research Article
Authors: Toshniwal, Durga
Affiliations: Department of Electronics & Computer Engineering, Indian Institute of Technology Roorkee, Uttarakhand 247 667, India. Tel.: +91 1332271575; E-mail: durgafec@iitr.ernet.in
Abstract: Many scientific and business domains require the collection and analysis of time series data. Feature extraction is an important component of time series data mining. In this paper, we introduce simple and novel techniques for feature extraction from time series data based on moments and slopes. The proposed techniques are capable of handling vertical and horizontal shifts existing between time sequences. They can also handle global scaling and shrinking of the time sequences.
Keywords: Feature extraction, time series data, data mining, centroids, dimension reduction
DOI: 10.3233/JCM-2009-0239
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 9, no. s1, pp. S99-S110, 2009
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