Efficient average quality index estimation of integrated circuits by modified Latin hypercube sampling Monte Carlo (MLHSMC)

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

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