RT Journal Article ID 699d886b45d6b358 A1 Schiavazzi, Daniele E. A1 Doostan, Alireza A1 Iaccarino, Gianluca T1 SPARSE MULTIRESOLUTION REGRESSION FOR UNCERTAINTY PROPAGATION JF International Journal for Uncertainty Quantification JO IJUQ YR 2014 FD 2014-07-28 VO 4 IS 4 SP 303 OP 331 K1 uncertainty quantification K1 multiresolution approximation K1 compressive sampling K1 adaptive importance sampling K1 tree-based orthogonal matching pursuit K1 uncertain tuned mass damper AB The present work proposes a novel nonintrusive, i.e., sampling-based, framework for approximating stochastic solutions of interest admitting sparse multiresolution expansions. The coefficients of such expansions are computed via greedy approximation techniques that require a number of solution realizations smaller than the cardinality of the multiresolution basis. The effect of various random sampling strategies is investigated. The proposed methodology is verified on a number of benchmark problems involving nonsmooth stochastic responses, and is applied to quantifying the efficiency of a passive vibration control system operating under uncertainty. PB Begell House LK https://www.dl.begellhouse.com/journals/52034eb04b657aea,670f36d96da30eed,699d886b45d6b358.html