Abstract
Statistical variability (SV) is one of the fundamental limiting factors for future nano- CMOS scaling and integration of. Variability aware design is essential to achieve reasonable yield and reliability in the manufacture of circuit and systems. To develop effective variability aware design technologies it is essential to have a reliable and accurate statistical compact modeling strategy. In this study a nonlinear power method (NPM) based statistical compact modeling strategy is presented. The results indicate that statistical compact model parameters generated by a NPM approach are significantly better at capturing the tails and non-normal shape of statistical parameter distributions when compared with principal component analysis (PCA).
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