• DocumentCode
    2560456
  • Title

    Improved CFC algorithm for template decomposition with guaranteed robustness

  • Author

    Lin, Yih-Lon ; Teng, Wei-Chih ; Jeng, Jyh-Horng ; Hsieh, Jer-Guang

  • Author_Institution
    Dept. of Electr. Eng., National Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • fYear
    2005
  • fDate
    28-30 May 2005
  • Firstpage
    102
  • Lastpage
    105
  • Abstract
    In this paper, an improved version of CFC algorithm is proposed. The main contribution is the reduction of a dimension in the search space. Moreover, the elements in the reduced search space are entries of control templates of uncoupled CNNs and the corresponding linearly separable Boolean functions are robust in the sense of maximal geometric margin. Illustrative examples demonstrate the efficiency of the proposed method.
  • Keywords
    Boolean functions; cellular neural nets; computational geometry; search problems; stability; CFC algorithm; cellular neural network; linearly separable Boolean functions; maximal geometric margin; search space dimension reduction; template decomposition; uncoupled CNN; Boolean functions; Cellular neural networks; Hardware; Large-scale systems; Neural networks; Nonlinear circuits; Nonlinear equations; Robust control; Robustness; Signal processing algorithms; Boolean Function; Cellular Neural Network; Linearly Separable; Maximal Margin; Uncoupled CNN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
  • Print_ISBN
    0-7803-9185-3
  • Type

    conf

  • DOI
    10.1109/CNNA.2005.1543171
  • Filename
    1543171