Encouraging results and good agreement between theory and simulation results have thus far been obtained.

of 2c+1 runs in 2c factors by modifying Step III in the above procedure. However, in practice, engineers may have some prior information about the sub-domains where the response volatility is relatively large, named the interesting sub-domains. In the traditional Latin square sampling, engineers often arrange sample points in the feasible domain uniformly. Finally, a numerical and a CMOS clock driver circuit examples are given. Latin hypercube sampling offers improvement over simple random sampling with. Latin hypercube sampling is widely used in industrial engineering. Theoretical and practical aspects of its statistical properties are also given. In this paper a variant of the Latin Hypercube Sampling MC method is presented which is an efficient variance reduction technique in MC estimation. Modified Algorithms for Fast Construction of Optimal Latin-Hypercube Design Abstract: As accuracy of optimization can not be guaranteed without high-quality samples, the distribution of a finite number of evaluation points where experiments should be conducted in design space is an important issue, particularly when the experiment to obtain. 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 addition, the samples from the uniform and loguniform distributions may be modified by. Modified Latin Hypercube Sampling Monte Carlo (MLHSMC) Estimation for Average Quality Index Modified Latin Hypercube Sampling Monte Carlo (MLHSMC) Estimation for Average Quality Index LHS: Code System to Generate Latin Hypercube & Random Samples.

Modified latin hypercube sampling