Gradient-Based Method to Find Solution for Rational Polynomial Chaos Coefficients for Uncertainty Quantification

Rational Polynomial Chaos (RPC) is an emerging method for forming the surrogate model for uncertainty quantification in circuit applications. However, the use of Rational Polynomial Chaos can be prohibitive as it generally requires a large number of samples to generate the surrogate models. In this paper, we propose the use of gradient-based algorithm to solve for the Rational Polynomial Chaos coefficients. Using the proposed approach we can compute the RPC coefficients with fewer samples than the traditional RPC method.