• DocumentCode
    2999884
  • Title

    A novel methodology for statistical parameter extraction

  • Author

    Krishna, K. ; Director, S.W.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA
  • fYear
    1995
  • fDate
    5-9 Nov. 1995
  • Firstpage
    696
  • Lastpage
    699
  • Abstract
    IC manufacturing process variations are typically expressed in terms of joint probability density functions (jpdf´s) or as worst case combinations/corners of the device model parameters. However, since device models can only provide approximations to actual device behavior, the difference between the two being the modelling error only a part of the measured variation in device behavior can be modelled using device model parameter variations and the remaining appears as modelling error variation. In this paper we present a novel statistical parameter extraction methodology that accounts for the effect of modelling error on device model parameter statistics and can be used to quantify the statistical suitability of conventional MOS device models.
  • Keywords
    circuit analysis computing; error analysis; integrated circuit manufacture; semiconductor device models; statistical analysis; IC manufacturing process; MOS device models; device model parameter statistics; device models; joint probability density functions; statistical parameter extraction; Equations; Fluctuations; Integrated circuit modeling; Manufacturing processes; Mathematical model; Parameter estimation; Parameter extraction; Probability density function; Statistics; Virtual manufacturing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Aided Design, 1995. ICCAD-95. Digest of Technical Papers., 1995 IEEE/ACM International Conference on
  • Conference_Location
    San Jose, CA, USA
  • ISSN
    1092-3152
  • Print_ISBN
    0-8186-8200-0
  • Type

    conf

  • DOI
    10.1109/ICCAD.1995.480205
  • Filename
    480205