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

Rüdiger Frey, Thorsten Schmidt, Ling Xu

Publication: Scientific journalJournal articlepeer-review

Abstract

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 working with a subspace that is constructed from a basis of Hermite polynomials. The paper closes with a numerical case study.
Original languageEnglish
Pages (from-to)2036 - 2062
JournalSIAM Journal on Numerical Analysis (Society for Industrial and Applied Mathematics)
Volume51
Issue number4
DOIs
Publication statusPublished - 1 Oct 2013

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