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Analyzing impact of epistemic uncertainty in high-speed circuit simulation using fuzzy variables and global polynomial chaos surrogates

In this paper, a PC based approach for epistemic uncertainty quantification of high-speed circuits is presented. This work assumes that the epistemic uncertainty in circuit parameters is described using noninteracting fuzzy variables with multiple confidence levels ascribed to each variables. A methodology to propagate the fuzzy variables through the circuit model using PC expansions is proposed. The key benefit of this work is that instead of developing a local PC expansion at every confidence level from first principles, a global PC expansion is constructed only once and reused at the different confidence levels. In this way, the computational cost of propagating the uncertainty is made independent of the number of confidence levels. The performance of the global PC expansion is validated using an active filter design example.