DocumentCode
1920220
Title
Regression time warping for similarity measure of sequence
Author
Lei, Hansheng ; Govindaraju, Venu
Author_Institution
Center for Unified Biometrics & Sensors, New York State Univ., USA
fYear
2004
fDate
14-16 Sept. 2004
Firstpage
826
Lastpage
830
Abstract
In the paper, we propose regression time warping (RTW), a similarity measure for sequence or time series matching. RTW fuses the linear regression analysis, which controls the shifting and scaling factors between sequences (Lei and Govindaraju, 2004), and the principles of dynamic time warping (DTW), which provides robustness with elastic matching. RTW has complexity as low as O(n), while the complexity of DTW is O(n2). Experimental results show the accuracy of RTW in classification is comparable to DTW, and much faster than DTW in term of running time.
Keywords
computational complexity; pattern classification; pattern matching; regression analysis; sequences; time series; dynamic time warping; elastic matching; linear regression analysis; regression time warping; scaling factor; sequence similarity measure; shifting factor; time series matching; Biometrics; Biosensors; Elasticity; Fuses; Indexing; Linear regression; Robust control; Robustness; Time measurement; Venus;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Technology, 2004. CIT '04. The Fourth International Conference on
Print_ISBN
0-7695-2216-5
Type
conf
DOI
10.1109/CIT.2004.1357297
Filename
1357297
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