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arXiv 1303.0975math.NAcs.NAmath.PR
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具有扩散和点过程观测的Zakai方程的Galerkin逼近

On Galerkin Approximations for the Zakai Equation with Diffusive and Point Process Observations

WU Vienna(维也纳经济大学);Chemnitz University of Technology(开姆尼茨工业大学);China University of Petroleum(中国石油大学);University of Leipzig(莱比锡大学)

Rüdiger Frey, Thorsten Schmidt, Ling Xu

AI总结:

本文研究随机滤波中Zakai方程的Galerkin逼近,将无限维方程投影到由光滑基函数生成的有限维子空间,得到可数值求解的随机微分方程组,并推广了收敛性结果至点过程或混合类型观测模型,同时讨论了数值实现问题,特别是基于Hermite多项式基的子空间构造。

摘要:

本文研究应用于随机滤波中Zakai方程的Galerkin逼近。该方法的基本思想是将无限维Zakai方程投影到由光滑基函数生成的某个有限维子空间上;这导致一个可数值求解的有限维随机微分方程组。本文的贡献有两方面。在理论方面,现有的收敛性结果被推广到具有点过程或混合类型观测的滤波模型。在应用方面,考虑了与该方法数值实现相关的各种问题;特别是,我们提出使用由Hermite多项式基构造的子空间。本文以一个数值案例研究结束。

英文摘要:

This paper studies Galerkin approximations applied to the Zakai equation of stochastic filtering. The basic idea of this approach is to project the infinite-dimensional Zakai equation onto some finite-dimensional subspace generated by smooth basis functions; this leads to a finite-dimensional system of stochastic differential equations that can be solved numerically. The contribution of the paper is twofold. On the theoretical side, existing convergence results are extended to filtering models with observations of point-process or mixed type. On the applied side, various issues related to the numerical implementation of the method are considered; in particular, we propose to work with a subspace that is constructed from a basis of Hermite polynomials. The paper closes with a numerical case study.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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