A strongly monotonic polygonal Euler scheme

IF 1.8 2区 数学 Q1 MATHEMATICS
Tim Johnston, Sotirios Sabanis
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引用次数: 2

Abstract

In recent years tamed schemes have become an important technique for simulating SDEs and SPDEs whose continuous coefficients display superlinear growth. The taming method involves curbing the growth of the coefficients as a function of stepsize, but so far has not been adapted to preserve the monotonicity of the coefficients. This has arisen as an issue in [4], where the lack of a strongly monotonic tamed scheme forces strong conditions on the setting. In this article we give a novel and explicit method for truncating monotonic functions in separable real Hilbert spaces, and show how this can be used to define a polygonal (tamed) Euler scheme on finite dimensional space, preserving the monotonicity of the drift coefficient, and converging to the true solution at the same rate as the classical Euler scheme for Lipschitz coefficients. Our construction is the first explicit method for truncating monotone functions we are aware of, and the first in infinite dimensions.

强单调多边形欧拉格式
近年来,驯服方案已成为模拟连续系数显示超线性增长的SDE和SPDE的重要技术。驯服方法包括抑制作为步长函数的系数的增长,但到目前为止还没有适应于保持系数的单调性。这在[4]中出现了一个问题,其中缺乏强单调驯服方案迫使设置具有强条件。在本文中,我们给出了一种新的显式方法来截断可分离实Hilbert空间中的单调函数,并展示了如何使用该方法来定义有限维空间上的多边形(驯服)Euler格式,保持漂移系数的单调性,并以与Lipschitz系数的经典Euler格式相同的速率收敛到真解。我们的构造是我们所知道的第一个截断单调函数的显式方法,也是无穷维中的第一个。
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来源期刊
Journal of Complexity
Journal of Complexity 工程技术-计算机:理论方法
CiteScore
3.10
自引率
17.60%
发文量
57
审稿时长
>12 weeks
期刊介绍: The multidisciplinary Journal of Complexity publishes original research papers that contain substantial mathematical results on complexity as broadly conceived. Outstanding review papers will also be published. In the area of computational complexity, the focus is on complexity over the reals, with the emphasis on lower bounds and optimal algorithms. The Journal of Complexity also publishes articles that provide major new algorithms or make important progress on upper bounds. Other models of computation, such as the Turing machine model, are also of interest. Computational complexity results in a wide variety of areas are solicited. Areas Include: • Approximation theory • Biomedical computing • Compressed computing and sensing • Computational finance • Computational number theory • Computational stochastics • Control theory • Cryptography • Design of experiments • Differential equations • Discrete problems • Distributed and parallel computation • High and infinite-dimensional problems • Information-based complexity • Inverse and ill-posed problems • Machine learning • Markov chain Monte Carlo • Monte Carlo and quasi-Monte Carlo • Multivariate integration and approximation • Noisy data • Nonlinear and algebraic equations • Numerical analysis • Operator equations • Optimization • Quantum computing • Scientific computation • Tractability of multivariate problems • Vision and image understanding.
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