Modified Latin Hypercube Sampling Monte Carlo (MLHSMC) Estimation for Average Quality Index

The Monte Carlo (MC) method exhibits generality and insensitivity to the number of stochastic variables, but it is expensive for accurate Average Quality Index (AQI) or Parametric Yield estimation of MOS VLSI circuits or discrete component circuits. In this paper a variant of the Latin Hypercube Sampling MC method is presented which is an efficient variance reduction technique in MC estimation. Theoretical and practical aspects of its statistical properties are also given. Finally, a numerical and a CMOS clock driver circuit examples are given. Encouraging results and good agreement between theory and simulation results have thus far been obtained.

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