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
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;
Conference_Titel :
Computer-Aided Design, 1995. ICCAD-95. Digest of Technical Papers., 1995 IEEE/ACM International Conference on
Conference_Location :
San Jose, CA, USA
Print_ISBN :
0-8186-8200-0
DOI :
10.1109/ICCAD.1995.480205