Alternating direction method for enhancing sparsity of the representation of uncertainty
- 4:30PM at UNIV 103
- Dr. Xiu Yang, Pacific Northwest National Lab
- Alternating direction method for enhancing sparsity of the representation of uncertainty
Compressive sensing has become a powerful tool for uncertainty quantification when only limited data is available. We provide a general framework using alternating direction method to enhance the sparsity of the representation of uncertainty in the form of generalized polynomial chaos expansion. This method identifies new sets of random variables through iterative rotations such that the new representation of the uncertainty using these variables is sparser. Consequently, we increase both the efficiency and accuracy of the compressive sensing-based uncertainty quantification method. We demonstrate the effectiveness of this method with applications in analyzing uncertainties in high-dimensional complex systems.