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Mathematics of Computation

Published by the American Mathematical Society since 1960 (published as Mathematical Tables and other Aids to Computation 1943-1959), Mathematics of Computation is devoted to research articles of the highest quality in computational mathematics.

ISSN 1088-6842 (online) ISSN 0025-5718 (print)

The 2020 MCQ for Mathematics of Computation is 1.78.

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Semi-discretization of stochastic partial differential equations on $\mathbb {R}^1$ by a finite-difference method
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by Hyek Yoo PDF
Math. Comp. 69 (2000), 653-666 Request permission

Abstract:

The paper concerns finite-difference scheme for the approximation of partial differential equations in $\mathbb {R}^1$, with additional stochastic noise. By replacing the space derivatives in the original stochastic partial differential equation (SPDE, for short) with difference quotients, we obtain a system of stochastic ordinary differential equations. We study the difference between the solution of the original SPDE and the solution to the corresponding equation obtained by discretizing the space variable. The need to approximate the solution in $\mathbb {R}^1$ with functions of compact support requires us to introduce a scale of weighted Sobolev spaces. Employing the weighted $L_p$-theory of SPDE, a sup-norm error estimate is derived and the rate of convergence is given.
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Additional Information
  • Hyek Yoo
  • Affiliation: School of Mathematics, University of Minnesota, Minneapolis, MN 55455
  • Email: yoo@math.umn.edu
  • Received by editor(s): March 3, 1998
  • Received by editor(s) in revised form: July 10, 1998
  • Published electronically: April 28, 1999
  • © Copyright 2000 American Mathematical Society
  • Journal: Math. Comp. 69 (2000), 653-666
  • MSC (1991): Primary 35R60, 60H15, 65M06, 65M15
  • DOI: https://doi.org/10.1090/S0025-5718-99-01150-3
  • MathSciNet review: 1654030