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Commun. Comput. Phys., 36 (2024), pp. 996-1020.
Published online: 2024-10
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This paper aims to develop and analyze a comprehensive discretized splitting-up numerical scheme for the Zakai equation. This equation arises from a nonlinear filtering problem, where observations incorporate noise modeled by point processes and Wiener processes. Initially, we introduce a regularization parameter and employ a splitting-up approach to break down the Zakai equation into two stochastic differential equations and a partial differential equation (PDE). Subsequently, we employ a finite difference scheme for the temporal dimension and the spectral Galerkin method for the spatial dimension to achieve full discretization of these equations. This results in a numerical solution for the Zakai equation using the splitting-up technique. We demonstrate that this numerical solution converges to the exact solution with a convergence order of $\frac{1}{2}.$ Additionally, we conduct several numerical experiments to illustrate and validate our theoretical findings.
}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2024-0075}, url = {http://global-sci.org/intro/article_detail/cicp/23484.html} }This paper aims to develop and analyze a comprehensive discretized splitting-up numerical scheme for the Zakai equation. This equation arises from a nonlinear filtering problem, where observations incorporate noise modeled by point processes and Wiener processes. Initially, we introduce a regularization parameter and employ a splitting-up approach to break down the Zakai equation into two stochastic differential equations and a partial differential equation (PDE). Subsequently, we employ a finite difference scheme for the temporal dimension and the spectral Galerkin method for the spatial dimension to achieve full discretization of these equations. This results in a numerical solution for the Zakai equation using the splitting-up technique. We demonstrate that this numerical solution converges to the exact solution with a convergence order of $\frac{1}{2}.$ Additionally, we conduct several numerical experiments to illustrate and validate our theoretical findings.