Advances in manufacturing process technology are key ensembles for the production of integrated circuits in the sub-micrometer region. It is of paramount importance to assess the effects of tolerances in the manufacturing process on the performance of modern integrated circuits. The polynomial chaos expansion has emerged as a suitable alternative to standard Monte Carlo-based methods that are accurate, but computationally cumbersome. This paper provides an overview of the most recent developments and challenges in the application of polynomial chaos-based techniques for uncertainty quantification in integrated circuits, with particular focus on high-dimensional problems
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
This paper presents a metamodel based on the sparse polynomial chaos approach, well adapted to high ...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
Advances in manufacturing process technology are key ensembles for the production of integrated circ...
Advances in manufacturing process technology are key ensembles for the production of integrated circ...
Uncertainty exists widely in engineering design. As one of the key components of engineering design,...
International audienceThis communication deals with the uncertainty quantification in high dimension...
One of the major tasks in electronic circuit design is the ability to predict the performance of gen...
In this chapter, we provide a collection of diverse applications of the polynomial chaos expansion ...
Unavoidable statistical variations in fabrication processes have a strong effect on the functionalit...
Inherent physical uncertainties can have a significant influence on computational predictions. It is...
This paper presents an algorithm for efficient uncertainty quantification (UQ) in the presence of ma...
© 2020 Elsevier Inc. All rights reserved. In the past decade, uncertainty quantification (UQ) has re...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
Uncertainty quantification is the state-of-the-art framework dealing with uncertainties arising in a...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
This paper presents a metamodel based on the sparse polynomial chaos approach, well adapted to high ...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...
Advances in manufacturing process technology are key ensembles for the production of integrated circ...
Advances in manufacturing process technology are key ensembles for the production of integrated circ...
Uncertainty exists widely in engineering design. As one of the key components of engineering design,...
International audienceThis communication deals with the uncertainty quantification in high dimension...
One of the major tasks in electronic circuit design is the ability to predict the performance of gen...
In this chapter, we provide a collection of diverse applications of the polynomial chaos expansion ...
Unavoidable statistical variations in fabrication processes have a strong effect on the functionalit...
Inherent physical uncertainties can have a significant influence on computational predictions. It is...
This paper presents an algorithm for efficient uncertainty quantification (UQ) in the presence of ma...
© 2020 Elsevier Inc. All rights reserved. In the past decade, uncertainty quantification (UQ) has re...
Uncertainty is a common feature in first-principles models that are widely used in various engineeri...
Uncertainty quantification is the state-of-the-art framework dealing with uncertainties arising in a...
Variations in material properties, boundary conditions, or the geometry can be expected in most elec...
This paper presents a metamodel based on the sparse polynomial chaos approach, well adapted to high ...
Uncertainty quantification seeks to provide a quantitative means to understand complex systems that ...