• DocumentCode
    3500638
  • Title

    The feature extraction and classification for signals based on the S-transform

  • Author

    Yun Lin ; Xiaochun Xu ; Bin Li ; Jinfeng Pang ; Ruolin Zhou

  • Author_Institution
    Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China
  • Volume
    01
  • fYear
    2013
  • fDate
    16-18 Aug. 2013
  • Firstpage
    550
  • Lastpage
    553
  • Abstract
    The S-transform is an very efficient time-frequency representation method. According to the contrast of the traditional methods, the S-transform has a progressive anti-noise property and time-frequency resolution. Making use of the advantage of the S-transform, the characteristic variables of the modulation signal can be gotten, which can be used to distinguish the different type of modulation signals. The simulation experiment results show that the S-transform can express the instantaneous frequency of modulation signals clearly. Through extracting the linear feature, this paper goes deep into scooping out the new characteristic and extracts the character vectors, which can be used to set up a classification and recognition model. It can be used to correctly classify the different type of modulation signals.
  • Keywords
    feature extraction; modulation; signal classification; signal representation; time-frequency analysis; transforms; S-transform; instantaneous frequency; linear feature extraction; modulation signal characteristic variables; progressive antinoise property; recognition model; signal classification; signal feature extraction; time-frequency representation method; time-frequency resolution; Binary phase shift keying; Continuous wavelet transforms; Frequency modulation; Feature Extraction; Instantaneous Frequency; Modulation Recognition; S-transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Measurement, Information and Control (ICMIC), 2013 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-1-4799-1390-9
  • Type

    conf

  • DOI
    10.1109/MIC.2013.6758024
  • Filename
    6758024