• DocumentCode
    2005996
  • Title

    Establishing Common Pattern of Traditional Chinese Medicine Fingerprint by SVM

  • Author

    Yang, Yun ; Zhu, Xuefeng

  • Author_Institution
    South China Univ. of Technol., Guangzhou
  • fYear
    2007
  • fDate
    May 30 2007-June 1 2007
  • Firstpage
    1677
  • Lastpage
    1682
  • Abstract
    Establishing the common pattern of the traditional Chinese medicine fingerprint signal is an important problem for the evaluation in herbal medicine field. This study deals with the application of support vector machine regression combined with discrete wavelet transform in creating the common pattern of fingerprint signal. The original signal was first decomposed to different scales by discrete wavelet transform constructed by lifting scheme, and then the decomposed signal components were approximated by different kernel function of support vector machine regression. The real-life samples is used for the experiment to train and test the support vector machine regression in achieving the common pattern, the result shows that the approach proposed in this study is a useful method in establishing the common pattern of fingerprint signal.
  • Keywords
    discrete wavelet transforms; medical computing; regression analysis; support vector machines; SVM; common pattern; discrete wavelet transform; herbal medicine; support vector machine regression; traditional Chinese medicine fingerprint signal; Automatic control; Automation; Discrete wavelet transforms; Educational institutions; Fingerprint recognition; Kernel; Neural networks; Signal processing; Space technology; Support vector machines; common pattern; support vector machine; traditional Chinese medicine fingerprint; wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Automation, 2007. ICCA 2007. IEEE International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4244-0818-4
  • Electronic_ISBN
    978-1-4244-0818-4
  • Type

    conf

  • DOI
    10.1109/ICCA.2007.4376646
  • Filename
    4376646