• DocumentCode
    2476587
  • Title

    Multicomponent Linear FM Signal Detection Based on Support Vector Clustering

  • Author

    Linghuan, Wang ; Hongguang, Ma ; Qi, Li ; Zheng, Li

  • Author_Institution
    Res. Inst. of High Technol., Xi´´an
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    743
  • Lastpage
    747
  • Abstract
    The support vector clustering (SVC) algorithm was introduced to get the number of the pinnacles in the result of the time-frequency analysis and Radon transform of the multicomponent linear FM (LFM) signal, and to fulfil the detection of the components of the LFM signal. Meanwhile, an approach called near zero mean, for reducing the point number of the input data-set for SVC, was proposed to improve the computation efficiency. And a novel cluster labeling method was developed to improve the SVC algorithm. The simulation results depict that the SVC-radon-time-frequency approach is efficient for the detection and parameter estimation of the multi-components LFM signal
  • Keywords
    Radon transforms; parameter estimation; pattern clustering; support vector machines; time-frequency analysis; Radon transform; SVC algorithm; cluster labeling method; multicomponent linear FM signal detection; parameter estimation; support vector clustering; time-frequency analysis; Clustering algorithms; Computational modeling; Filters; Labeling; Narrowband; Signal detection; Static VAr compensators; Time frequency analysis; Vectors; Wavelet transforms; Detection; Multicomponent LFM Signal; SVC;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information, Communications and Signal Processing, 2005 Fifth International Conference on
  • Conference_Location
    Bangkok
  • Print_ISBN
    0-7803-9283-3
  • Type

    conf

  • DOI
    10.1109/ICICS.2005.1689147
  • Filename
    1689147