• DocumentCode
    302557
  • Title

    About the robustness of CNN linear templates with bipolar images

  • Author

    Paasio, Ari ; Dawidziuk, Adam ; Halonen, Kari ; Porra, Veikko

  • Author_Institution
    Electron. Circuit Design Lab., Helsinki Univ. of Technol., Espoo, Finland
  • Volume
    3
  • fYear
    1996
  • fDate
    12-15 May 1996
  • Firstpage
    555
  • Abstract
    This paper defines robustness measures for CNN linear templates. The measures are described for the normal unity gain CNN and also for a very high gain CNN. Inaccuracies in templates are next introduced and formulas for new modified measures are defined. This information can be very useful to CNN hardware designers when determining the acceptable inaccuracies in the coefficient realizations. If some template is found not to be good in presence of inaccuracies the robustness can be increased. One way to increase the defined template robustness is discussed. The increase in robustness factors are calculated and finally one example is given for the use of the described method
  • Keywords
    VLSI; cellular neural nets; neural chips; stability; CNN linear templates; bipolar images; cellular neural networks; coefficient realizations; high gain CNN; normal unity gain CNN; robustness measures; template robustness improvement; Cellular neural networks; Electronic circuits; Gain measurement; Hardware; Robustness; Very large scale integration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
  • Conference_Location
    Atlanta, GA
  • Print_ISBN
    0-7803-3073-0
  • Type

    conf

  • DOI
    10.1109/ISCAS.1996.541656
  • Filename
    541656