Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition

Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition

Hierarchical uncertainty quantification can reduce the computational cost of stochastic circuit simulation by employing spectral methods at different levels. This paper presents an efficient framework to simulate hierarchically some challenging stochastic circuits/systems that include high-dimension...

Full description

Bibliographic Details
Main Authors: Oseledets, Ivan V., Karniadakis, George E., Daniel, Luca, Zhang, Zheng, Yang, Xiu
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2015
Online Access:http://hdl.handle.net/1721.1/99952
https://orcid.org/0000-0002-5880-3151

Internet

http://hdl.handle.net/1721.1/99952
https://orcid.org/0000-0002-5880-3151

Similar Items