Sparse finite element methods for operator equations with stochastic data
نویسندگان
چکیده
منابع مشابه
First order k-th moment finite element analysis of nonlinear operator equations with stochastic data
We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(α, u) = 0 for random input α(ω) with almost sure realizations in a ...
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ژورنال
عنوان ژورنال: Applications of Mathematics
سال: 2006
ISSN: 0862-7940,1572-9109
DOI: 10.1007/s10492-006-0010-1