A Polymorphic Polynomial Chaos for Fast Uncertainty Quantification of RF/Microwave Circuits in Presence of Design Variables

Journal article

Mohd. Yusuf, Sourajeet Roy
Intelligent Memory Systems, 2021

Cite

APA Click to copy
Yusuf, M., & Roy, S. (2021). A Polymorphic Polynomial Chaos for Fast Uncertainty Quantification of RF/Microwave Circuits in Presence of Design Variables. Intelligent Memory Systems.

Chicago/Turabian Click to copy
Yusuf, Mohd., and Sourajeet Roy. “A Polymorphic Polynomial Chaos for Fast Uncertainty Quantification of RF/Microwave Circuits in Presence of Design Variables.” Intelligent Memory Systems (2021).

MLA Click to copy
Yusuf, Mohd., and Sourajeet Roy. “A Polymorphic Polynomial Chaos for Fast Uncertainty Quantification of RF/Microwave Circuits in Presence of Design Variables.” Intelligent Memory Systems, 2021.

BibTeX Click to copy

@article{mohd2021a,
  title = {A Polymorphic Polynomial Chaos for Fast Uncertainty Quantification of RF/Microwave Circuits in Presence of Design Variables},
  year = {2021},
  journal = {Intelligent Memory Systems},
  author = {Yusuf, Mohd. and Roy, Sourajeet}
}

Abstract

In this paper, a new polynomial chaos (PC) approach based on the notion of polymorphic variables is developed to perform rapid uncertainty quantification of RF/microwave circuits that are subject to both random fabrication process variations and systematic design variations. The proposed approach leads to the very efficient training of PC metamodels where the trajectories of the metamodels as a function of the design variables is explicitly captured. As a result, at any arbitrary design point, the uncertainty quantification of the circuit can be performed without reconstructing a new PC metamodel