Multi-Fidelity Approach for Polynomial Chaos Based Statistical Analysis of Microwave Networks
Keywords:
Multi-Fidelity Approach, Microwave NetworksAbstract
In this paper, a novel polynomial chaos based approach for the fast statistical analysis of complex microwave structures is proposed. This approach leverages a highly efficient closed form low-fidelity model elicited from the high-dimensional model representation (HDMR) of the network. By cross-cutting the efficiency of this low-fidelity model with the accuracy of general high-fidelity simulations, the accuracy-CPU cost tradeoff for the statistical analysis can be achieved.
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References
P. Manfredi, D. Vande Ginste, D. De Zutter and F. Canavero, “Stochastic modeling of nonlinear circuits via SPICE-compatible spectral equivalents,” IEEE Trans. Circuits Syst., vol. 61, no. 7, pp. 2057–2065, Jul. 2014
A. K. Prasad, M. Ahadi, and S. Roy, “Multidimensional uncertainty quantification of microwave/RF networks using linear regression and optimal design of experiments,” IEEE Trans. Microwave Theory Techniques, vol. 64, no. 8, pp 2433-2446, Aug. 2016
A. C. Yucel, H. Bagci, and E. Michielssen, “An ME-PC enhanced HDMR method for efficient statistical analysis of multiconductor transmission line networks,” IEEE Trans. Comp., Packag. and Manuf. Technology, vol. 5, no. 5, pp. 685-696, May 2015
H. Rabitz and O. F. Alis, “General formulation of high-dimensional model representations,” Journal of Math. Chem., vol. 50, no. 2-3, pp. 197-233, 1999
