Name
Abstract | ||
|---|---|---|
We further develop the Multivariate Decomposition Method (MDM) for the Lebesgue integration of functions of infinitely many variables x1,x2,x3,… with respect to a corresponding product of a one dimensional probability measure. The method is designed for functions that admit a dominantly convergent decomposition f=∑ufu, where u runs over all finite subsets of positive integers, and for each u={i1,…,ik} the function fu depends only on xi1,…,xik. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.cam.2017.05.031 | Journal of Computational and Applied Mathematics |
Keywords | Field | DocType |
Quadrature,Cubature,Infinite-dimensional | Tensor product,Uniqueness,Function space,Mathematical optimization,Normed vector space,Mathematical analysis,Probability measure,Decomposition method (constraint satisfaction),Mathematics,Reproducing kernel Hilbert space,Lebesgue integration | Journal |
Volume | Issue | ISSN |
326 | 326 | 0377-0427 |
Citations | PageRank | References |
0 | 0.34 | 20 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frances Y. Kuo | 1 | 479 | 45.19 |
| Dirk Nuyens | 2 | 168 | 17.97 |
| Leszek Plaskota | 3 | 75 | 17.77 |
| Ian H. Sloan | 4 | 1180 | 183.02 |
| Grzegorz W. Wasilkowski | 5 | 527 | 167.51 |