A novel methodology for statistical parameter extraction

  • Authors:
  • Kannan Krishna;S. W. Director

  • Affiliations:
  • Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA;Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • ICCAD '95 Proceedings of the 1995 IEEE/ACM international conference on Computer-aided design
  • Year:
  • 1995

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Abstract

IC manufacturing process variations are typically expressed in terms of joint probability density function (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 modeling error, only a part of the measured variation in device behavior can be modeled using device model parameter variations and the remaining appears as modeling error variation. In this paper, we present a novel statistical parameter extraction methodology that accounts for the effect of modeling error on device model parameter statistics and can be used to quantify the statistical suitability of conventional MOS device models.