Efficient Hermite-based variability analysis using approximate decoupling technique

This paper presents a new approach aimed at limiting the growth of the computational cost of variability analysis, using the Hermite-based Polynomial Chaos (PC), with the increase in the number of random variables and the number of Hermite coefficients used to represent the circuit response in each random variable. The proposed technique is based on deriving a closed-form formula for the structure of the augmented matrices generated by the PC approach, and then shows that this structure can be approximated with a different structure that can be decoupled easily.