• DocumentCode
    2685281
  • Title

    Research of Radar Range Profile´s Recognition Based on an Improved C-SVM Algorithm

  • Author

    Ning, Fang ; Tao, Fan

  • Author_Institution
    Coll. of Autom. & Electron. Inf., SUSE, Zigong, China
  • fYear
    2012
  • fDate
    27-29 Oct. 2012
  • Firstpage
    801
  • Lastpage
    804
  • Abstract
    This paper improves upon Support Vector Machines (SVM) algorithm on unclassifiable sample sets condition for more to enhance its applicability, which is named after C-SVM (C is a parameter). One hand, non-equidistant margin hyper plane (NM) in high dimension eigen space is introduced to improve on study precision, On the other hand, effectual training sample sets in high dimension eigen space are filtrated, via algorithm introduced by this paper, to reduce study time. Above-mentioned methods are applied to Radar Range Profile´s Recognition, experimental results show that these methods can give very excellent recognition effect.
  • Keywords
    pattern classification; radar computing; support vector machines; NM; effectual training sample sets; high dimension eigen space; improved C-SVM algorithm; nonequidistant margin hyperplane; radar range profile recognition; support vector machines; unclassifiable sample set condition; Classification algorithms; Partitioning algorithms; Pattern recognition; Radar; Support vector machines; Target recognition; Training; Eigen space; Non-equidistant margin hyperplane (NM); Radar Range Profile; Support Vector Machines (SVM);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4673-4873-7
  • Type

    conf

  • DOI
    10.1109/CIT.2012.163
  • Filename
    6392002