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Reduced Dimensional Chebyshev-Polynomial Chaos Approach for Fast Mixed Epistemic-Aleatory Uncertainty Quantification of Transmission Line Networks
16 references·4 citing·45 second hop
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References

  • 2008Aleatory or epistemic? Does it matter?2,450 cited
  • 2010Numerical Methods for Stochastic Computations: A Spectral Method Approach1,107 cited
  • 1999General foundations of high‐dimensional model representations905 cited
  • 2009An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis834 cited
  • 1994Propagation of Uncertainty in Risk Assessments: The Need to Distinguish Between Uncertainty Due to Lack of Knowledge and Uncertainty Due to Variability701 cited
  • 2014Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces267 cited
  • 2011Mixed aleatory-epistemic uncertainty quantification with stochastic expansions and optimization-based interval estimation192 cited
  • 2014A new uncertain analysis method and its application in vehicle dynamics166 cited
  • 2015Generalized Decoupled Polynomial Chaos for Nonlinear Circuits With Many Random Parameters102 cited
  • 2014Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition98 cited
  • 2012Variability Analysis of Multiport Systems Via Polynomial-Chaos Expansion94 cited
  • 2013Random-Space Dimensionality Reduction for Expedient Yield Estimation of Passive Microwave Structures92 cited
  • 2013Generalized Hermite Polynomial Chaos for Variability Analysis of Macromodels Embeddedin Nonlinear Circuits71 cited

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2015
An ME-PC Enhanced HDMR Method for Efficient Statistical Analysis of Multiconductor Transmission Line Networks
71 cited
  • 2014Decoupled Polynomial Chaos and Its Applications to Statistical Analysis of High-Speed Interconnects70 cited
  • 2016Big-Data Tensor Recovery for High-Dimensional Uncertainty Quantification of Process Variations66 cited
  • Cited by

    • 2022Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates22 cited
    • 2022A Robust Bayesian Optimization Framework for Microwave Circuit Design under Uncertainty16 cited
    • 2022Tolerance-Aware Optimization of Microwave Circuits by Means of Principal Directions and Domain-Restricted Metamodels15 cited
    • 2021A Polymorphic Polynomial Chaos Formulation for Mixed Epistemic-Aleatory Uncertainty Quantification of RF/Microwave Circuits12 cited