Empirical model-building and response surface
Empirical model-building and response surface
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
Modified Latin Hypercube Sampling Monte Carlo (MLHSMC) Estimation for Average Quality Index
Analog Integrated Circuits and Signal Processing
Advanced variance reduction and sampling techniques for efficient statistical timing analysis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A fast analog circuit yield estimation method for medium and high dimensional problems
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
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The Monte Carlo method exhibits generality and insensitivityto the number of stochastic variables, but is expensive for accurateAverage Quality Measure (AQI) or Parametric Yield estimationof MOS VLSI circuits. In this contribution a new method of variancereduction technique, viz. the Latin Hypercube Sampling (LHS)method is presented which improves the efficiency of AQI estimationin integrated circuits especially for MOS digital circuits. Thismethod is similar to the Primitive Monte Carlo (PMC) methodexcept in samples generation step where the Latin Hypercube Samplingmethod is used. This sampling method is very simple and doesnot involve any further simulations. Moreover, it has a smallervariance with respect to the PMC estimator. Encouraging resultshave thus far been obtained. A 3-dimensional quadratic function,a high pass filter, and a CMOS delay circuit examples are includedto demonstrate the efficiency of this technique.