• 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