• DocumentCode
    2289580
  • Title

    Approach Based on ICA and SVM to Identify Field Mixed Acoustic Targets

  • Author

    Huang, Fugui ; Chen, Gong ; Zhang, Xiongwei

  • Author_Institution
    Dept. of Electron. Inf. Eng., ICE of PLAUST, Nanjing
  • fYear
    2006
  • fDate
    16-19 Oct. 2006
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    With ICA to realize the blind separation from mixed acoustic targets, an identification method based on SVM is proposed through extracting LPC feature. SVM is employed to compute the output score and k-means algorithm is used as cluster LPC coefficients. Finally targets are identified by hybrid model. Simulation indicates that this method is effective in mixed acoustic targets identification system
  • Keywords
    acoustic signal processing; blind source separation; feature extraction; identification; independent component analysis; support vector machines; ICA; SVM; cluster LPC coefficient; independent component analysis; k-means algorithm; mixed acoustic target identification system; support vector machine; Acoustic noise; Acoustic waves; Clustering algorithms; Degradation; Feature extraction; Helicopters; Independent component analysis; Linear predictive coding; Signal analysis; Support vector machines; ICA; LPC; SVM; identification; mixed target;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radar, 2006. CIE '06. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    0-7803-9582-4
  • Electronic_ISBN
    0-7803-9583-2
  • Type

    conf

  • DOI
    10.1109/ICR.2006.343533
  • Filename
    4148214