high-dimensional quadrature;
white noise functional;
Wiener-Ito decomposition;
Quasi-Monte Carlo integration;
orthogonal polynomial;
wavelet;
D O I:
10.1016/S0377-0427(00)00604-X
中图分类号:
O29 [应用数学];
学科分类号:
070104 ;
摘要:
We consider (a discretization of) a functional of white noise over a finite time interval. We explore the possible interest of representing the white noise in the orthonormal bases of orthogonal polynomials or wavelets for the numerical evaluation of the expected value of this functional. Using the Wiener-Ita decomposition of the functional, the sparsity is studied of the representation of the functional in these bases. An approximation scheme is proposed that uses existing low-dimensional quasi-Monte Carlo rules and takes profit of the sparse structure of the quadratic part of the functional. (C) 2001 Elsevier Science B.V. All rights reserved.
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页码:33 / 49
页数:17
相关论文
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[11]
Owen AB, 1998, 1998 WINTER SIMULATION CONFERENCE PROCEEDINGS, VOLS 1 AND 2, P571, DOI 10.1109/WSC.1998.745036