• DocumentCode
    2516640
  • Title

    Random variations in CNN templates: theoretical models and empirical studies

  • Author

    Shi, B.E. ; Wendsche, S. ; Roska, T. ; Chua, L.O.

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., Kowloon, Hong Kong
  • fYear
    1994
  • fDate
    18-21 Dec 1994
  • Firstpage
    27
  • Lastpage
    32
  • Abstract
    This paper studies the performance of binary image processing CNN templates when the actual template values at each cell are allowed to vary from their nominal values. We examine the validity of one plausible measure of the robustness to random template variations: the minimum absolute value of the current into the capacitor taken over all possible binary state patterns divided by the norm of the template elements. While this measure can be proven to be a valid indicator of robustness for linear threshold templates, its predictive power on the more dynamically complex CCD template is mixed. In some cases, an estimate of the error rate based upon this measure matches remarkably well with the results of numerical simulations. In others, this measure of robustness predicts that one template is more robust than another, while numerical simulations indicate that the opposite is true
  • Keywords
    cellular neural nets; image processing; CNN templates; binary image processing; empirical studies; error rate; random template variations; robustness; theoretical models; Cellular neural networks; Charge coupled devices; Cloning; Image processing; Indexing; Numerical simulation; Piecewise linear techniques; Power measurement; Robustness; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
  • Conference_Location
    Rome
  • Print_ISBN
    0-7803-2070-0
  • Type

    conf

  • DOI
    10.1109/CNNA.1994.381684
  • Filename
    381684