| Xiu Yang, |
| Title: Enhancing Sparsity in Uncertainty Quantification Problems by Iterative Rotations |
| Abstract: Compressive sensing has become a powerful addition to uncertainty quantification in recent years. It helps to extract information from limited data. We propose a new method to enhance the sparsity of the representation of the uncertainty of the quantity of interest. Specifically, we consider rotation-based linear mappings which are determined iteratively for generalized polynomial chaos expansions.This procedure increases the accuracy of the compressive sensing-based uncertainty quantification method. We demonstrate the efficiency of this method with several examples. |
Friday April 22nd, at 11:00AM Math Conference room
Categories: Spring 2022