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The solution of the continuous time filtering problem can be represented as a ratio of two expectations of certain functionals of the signal process that are parametrized by the observation path. We introduce a class of discretization…

Probability · Mathematics 2017-11-23 Dan Crisan , Salvador Ortiz-Latorre

In this paper, we consider a nonlinear filtering model with observations driven by correlated Wiener processes and point processes. We first derive a Zakai equation whose solution is a unnormalized probability density function of the filter…

Numerical Analysis · Mathematics 2022-11-29 Fengshan Zhang , Yongkui Zou , Shimin Chai , Yanzhao Cao

We study an approximation method for the one-dimensional nonlinear filtering problem, with discrete time and continuous time observation. We first present the method applied to the Fokker-Planck equation. The convergence of the…

Numerical Analysis · Mathematics 2023-03-29 Fabien F. Campillo

In this paper we introduce a Hilbert space-valued Malliavin calculus for Poisson random measures. It is solely based on elementary principles from the theory of point processes and basic moment estimates, and thus allows for a simple…

Probability · Mathematics 2017-03-22 Adam Andersson , Felix Lindner

We consider the nonlinear Cauchy problem for $ \Psi $- Hilfer fractional differential equations and investigate the existence, interval of existence and uniqueness of solution in the weighted space of functions. The continuous dependence of…

Dynamical Systems · Mathematics 2020-06-23 Kishor D. Kucche , Ashwini D. Mali , J. Vanterler da C. Sousa

Nonlinear filtering problems are encountered in many applications, and one solution approach is the extended Kalman filter, which is not always convergent. Therefore, it is crucial to identify conditions under which the extended Kalman…

Probability · Mathematics 2026-03-24 Ibrahim Mbouandi Njiasse , Florent Ouabo Kamkumo , Ralf Wunderlich

We consider a stochastic version of the proximal point algorithm for optimization problems posed on a Hilbert space. A typical application of this is supervised learning. While the method is not new, it has not been extensively analyzed in…

Optimization and Control · Mathematics 2021-09-28 Monika Eisenmann , Tony Stillfjord , Måns Williamson

We prove a weak rate of convergence of a fully discrete scheme for stochastic Cahn--Hilliard equation with additive noise, where the spectral Galerkin method is used in space and the backward Euler method is used in time. Compared with the…

Numerical Analysis · Mathematics 2023-03-21 Meng Cai , Siqing Gan , Yaozhong Hu

In this paper we introduce a simple space-filtration discretization scheme on Wiener space which allows us to study weak decompositions and smooth explicit approximations for a large class of Wiener functionals. We show that any Wiener…

Probability · Mathematics 2013-07-23 Dorival Leão , Alberto Ohashi

We consider high order approximations of the solution of the stochastic filtering problem, derive their pathwise representation in the spirit of the earlier work of Clark and Davis and prove their robustness property. In particular, we show…

Numerical Analysis · Mathematics 2021-01-12 Dan Crisan , Alexander Lobbe , Salvador Ortiz-Latorre

We introduce a new extragradient iterative process, motivated and inspired by [S. H. Khan, A Picard-Mann Hybrid Iterative Process, Fixed Point Theory and Applications, doi:10.1186/1687-1812-2013-69], for finding a common element of the set…

Functional Analysis · Mathematics 2014-03-14 Ibrahim Karahan , Murat Ozdemir

We prove pointwise convergence for the scattering data of a Dirac system of differential equations. Equivalently, we prove an analog of Carleson's theorem on almost everywhere convergence of Fourier series for a version of the non-linear…

Complex Variables · Mathematics 2025-12-22 Alexei Poltoratski

This paper presents the convergence analysis of the spatial finite difference method (FDM) for the stochastic Cahn--Hilliard equation with Lipschitz nonlinearity and multiplicative noise. Based on fine estimates of the discrete Green…

Numerical Analysis · Mathematics 2026-04-14 Jialin Hong , Diancong Jin , Derui Sheng

The solution of the continuous time filtering problem can be represented as a ratio of two expectations of certain functionals of the signal process that are parametrized by the observation path. We introduce a new time discretisation of…

Probability · Mathematics 2014-08-26 Dan Crisan , Salvador Ortiz-Latorre

The aim of this paper is to provide a variational interpretation of the nonlinear filter in continuous time. A time-stepping procedure is introduced, consisting of successive minimization problems in the space of probability densities. The…

Optimization and Control · Mathematics 2014-12-19 Richard S. Laugesen , Prashant G. Mehta , Sean P. Meyn , Maxim Raginsky

A novel approximate Bayesian filter based on backward stochastic differential equations is introduced. It uses a nonlinear Feynman--Kac representation of the filtering problem and the approximation of an unnormalized filtering density using…

Numerical Analysis · Mathematics 2026-04-21 Kasper Bågmark , Adam Andersson , Stig Larsson

In this paper we prove a rate of convergence for the continuous time filtering solution of a multiple timescale correlated nonlinear system to a lower dimensional filtering equation in the limit of large timescale separation. Correlation is…

Probability · Mathematics 2022-01-19 Ryne Beeson , N. Sri Namachchivaya , Nicolas Perkowski

On the half line we introduce a new sequence of near--best uniform approximation polynomials, easily computable by the values of the approximated function at a truncated number of Laguerre zeros. Such approximation polynomials come from a…

Numerical Analysis · Mathematics 2024-02-14 Occorsio Donatella , Woula Themistoclakis

This paper considers the approximation of the continuous time filtering equation for the case of a multiple timescale (slow-intermediate, and fast scales) that may have correlation between the slow-intermediate process and the observation…

Probability · Mathematics 2020-11-02 Ryne Beeson , N. Sri Namachchivaya , Nicolas Perkowski

We consider stochastic differential equations in a Hilbert space, perturbed by the gradient of a convex potential. We investigate the problem of convergence of a sequence of such processes. We propose applications of this method to…

Probability · Mathematics 2007-05-23 Lorenzo Zambotti
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