Overview of IC Statistical Modeling

  • J. C. Zhang
  • M. A. Styblinski


Although the optimization problems introduced in the previous chapter can be formulated for any circuit, the methods for the problem solution strongly depend on the statistical properties represented by a suitable statistical model. At the circuit (simulator) parameter level, the circuit statistical model is determined by the transformation e i = e i (x, θ) and the p.d.f. f(θ). For the resistive voltage divider of Fig. 1.1, the statistical model can be stated as:
$$\left\{ {\matrix{ {{x_i}:{\rm{nominal element values}}} \hfill \cr {{\theta _i}:{\rm{element tolerances}}} \hfill \cr {{e_i} = {x_i} + {\theta _i},\,i = 1,2,} \hfill \cr {{\rm{or}}\,{e_i} = {x_i}\left( {1 + {\theta _i}} \right)\,{\rm{if}}\,{\theta _i}\,{\rm{has the relative tolerance fixed}}} \hfill \cr {{\theta _1}\,{\rm{and}}\,{\theta _2}\,{\rm{are statistically independent}}{\rm{.}}} \hfill \cr } } \right.$$


Circuit Simulator Device Simulator PMOS Transistor Process Disturbance Process Control Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • J. C. Zhang
    • 1
  • M. A. Styblinski
    • 2
  1. 1.Western Atlas International Inc.USA
  2. 2.Texas A & M UniversityUSA

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