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
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