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Stochastic Sparse-grid Collocation Algorithm (SSCA) for Periodic Steady-State Analysis of Nonlinear System with Process Variations

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References

1991Stochastic Finite Elements: A Spectral Approach5,753 cited
2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations4,821 cited
2005High-Order Collocation Methods for Differential Equations with Random Inputs1,522 cited
1999Uncertainty Analysis of Transport-Transformation Models329 cited

Cited by

2018Uncertainty propagation analysis by an extended sparse grid technique28 cited
2009A New Sparse Grid Based Method for Uncertainty Propagation21 cited
2020Uncertainty Quantification of Waveguide Dispersion Using Sparse Grid Stochastic Testing20 cited
2013Efficient Uncertainty Quantification for the Periodic Steady State of Forced and Autonomous Circuits18 cited
2018Uncertainty quantification of electronic and photonic ICs with non-Gaussian correlated process variations17 cited
2013Efficient uncertainty quantification for the periodic steady state of forced and autonomous circuits15 cited
2013Uncertainty quantification for integrated circuits: Stochastic spectral methods13 cited
2011Hybrid Gauss Pseudospectral and Generalized Polynomial Chaos Algorithm to Solve Stochastic Trajectory Optimization Problems13 cited
2020Chance-Constrained and Yield-Aware Optimization of Photonic ICs With Non-Gaussian Correlated Process Variations11 cited
2015

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Fast Variability Analysis of General Nonlinear Circuits Using Decoupled Polynomial Chaos

8 cited