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Stochastic Modeling of Nonlinear Circuits via SPICE-Compatible Spectral Equivalents

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References

2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
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2006Hermite Polynomial Based Interconnect Analysis in the Presence of Process Variations90 cited
2008Stochastic formulation of SPICE-type electronic circuit simulation with polynomial chaos77 cited
2013Generalized Hermite Polynomial Chaos for Variability Analysis of Macromodels Embeddedin Nonlinear Circuits71 cited

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2016Multidimensional Uncertainty Quantification of Microwave/RF Networks Using Linear Regression and Optimal Design of Experiments43 cited
2017Accurate Reduced Dimensional Polynomial Chaos for Efficient Uncertainty Quantification of Microwave/RF Networks39 cited
2019High-Dimensional Uncertainty Quantification of Electronic and Photonic IC With Non-Gaussian Correlated Process Variations31 cited
2017A Comprehensive and Modular Stochastic Modeling Framework for the Variability-Aware Assessment of Signal Integrity in High-Speed Links24 cited
2018

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Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks

23 cited

2016Hyperbolic polynomial chaos expansion (HPCE) and its application to statistical analysis of nonlinear circuits22 cited

2020A Perturbative Stochastic Galerkin Method for the Uncertainty Quantification of Linear Circuits19 cited

2019Rational Polynomial Chaos Expansions for the Stochastic Macromodeling of Network Responses13 cited

2021Fast Stochastic Surrogate Modeling via Rational Polynomial Chaos Expansions and Principal Component Analysis13 cited

2021A Polymorphic Polynomial Chaos Formulation for Mixed Epistemic-Aleatory Uncertainty Quantification of RF/Microwave Circuits12 cited

2016A big-data approach to handle process variations: Uncertainty quantification by tensor recovery12 cited