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We consider a nonlinear filtering problem of multiscale non-Gaussian signal processes and observation processes with jumps. Firstly, we prove that the dimension for the signal system can be reduced by a homogenized approach. Secondly,…

Probability · Mathematics 2019-10-21 Huijie Qiao

We study robust nonlinear filtering for stochastic models driven by L\'evy processes, where the signal and observation processes are coupled through common Brownian and jump noise. Robustness, defined as the continuous dependence of the…

Probability · Mathematics 2026-04-30 Sharan Srinivasan , Vijay Gupta , Harsha Honnappa

A goal of data assimilation is to infer stochastic dynamical behaviors with available observations. We consider transition phenomena between metastable states for a stochastic system with (non-Gaussian) $\alpha-$stable L\'evy noise. With…

Dynamical Systems · Mathematics 2016-06-29 Ting Gao , Jinqiao Duan , Xingye Kan

This paper deals with a nonlinear filtering problem in which a multi-dimensional signal process is additively affected by a process $\nu$ whose components have paths of bounded variation. The presence of the process $\nu$ prevents from…

Optimization and Control · Mathematics 2022-06-02 Alessandro Calvia , Giorgio Ferrari

Linear dynamical systems, driven by a non-white noise which has the Levy distribution, are analysed. Noise is modelled by a specific stochastic process which is defined by the Langevin equation with a linear force and the Levy distributed…

Statistical Mechanics · Physics 2011-01-26 Tomasz Srokowski

This work is about low dimensional reduction for a slow-fast data assimilation system with non-Gaussian $\alpha-$stable L\'evy noise via stochastic averaging. When the observations are only available for slow components, we show that the…

Dynamical Systems · Mathematics 2018-01-10 Yanjie Zhang , Zhuan Cheng , Xinyong Zhang , Xiaoli Chen , Jinqiao Duan , Xiaofan Li

The objective of this paper is to study the filtering problem for a system of partially observable processes $(X, Y)$, where $X$ is a non-Markovian pure-jump process representing the signal and $Y$ is a general jump-diffusion which provides…

Probability · Mathematics 2022-06-02 Elena Bandini , Alessandro Calvia , Katia Colaneri

We consider a nonlinear stochastic differential equation driven by an $\alpha$-stable L\'{e}vy process ($1<\alpha<2$). We first obtain some regularity results for the probability density of its invariant measure via establishing the a…

Probability · Mathematics 2020-08-17 Qi Zhang , Jinqiao Duan

The work concerns nonlinear filtering problems of stochastic differential equations with correlated L\'evy noises. First, we establish the Kushner-Stratonovich and Zakai equations through martingale representation theorems and the…

Probability · Mathematics 2020-05-05 Huijie Qiao

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

This paper is concerned with the nonlinear filtering problem for a general Markovian partially observed system (X,Y), whose dynamics is modeled by correlated jump-diffusions having common jump times. At any time t, the sigma-algebra…

Probability · Mathematics 2013-01-21 Claudia Ceci , Katia Colaneri

Levy processes are widely used in financial mathematics, telecommunication, economics, queueing theory and natural sciences for modelling. A typical model is obtained by considering finite dimensional linear stochastic SISO systems driven…

Statistics Theory · Mathematics 2014-01-07 Laszlo Gerencser , Mate Manfay

We analyze confining mechanisms for L\'{e}vy flights. When they evolve in suitable external potentials their variance may exist and show signatures of a superdiffusive transport. Two classes of stochastic jump - type processes are…

Statistical Mechanics · Physics 2015-05-13 Piotr Garbaczewski , Vladimir Stephanovich

Many physical systems characterized by nonlinear multiscale interactions can be effectively modeled by treating unresolved degrees of freedom as random fluctuations. However, even when the microscopic governing equations and qualitative…

Statistical Mechanics · Physics 2021-06-07 Jared L. Callaham , Jean-Christophe Loiseau , Georgios Rigas , Steven L. Brunton

We consider a non-linear filtering problem, whereby the signal obeys the stochastic Navier-Stokes equations and is observed through a linear mapping with additive noise. The setup is relevant to data assimilation for numerical weather…

Computation · Statistics 2018-04-10 Francesc Pons Llopis , Nikolas Kantas , Alexandros Beskos , Ajay Jasra

Consider a process satisfying a stochastic differential equation with unknown drift parameter, and suppose that discrete observations are given. It is known that a simple least squares estimator (LSE) can be consistent, but numerically…

Statistics Theory · Mathematics 2017-03-17 Yasutaka Shimizu

Phase transitions and effects of external noise on many body systems are one of the main topics in physics. In mean field coupled nonlinear dynamical stochastic systems driven by Brownian noise, various types of phase transitions including…

Statistical Mechanics · Physics 2015-05-13 Akihisa Ichiki , Masatoshi Shiino

In this paper we study general nonlinear stochastic differential equations, where the usual Brownian motion is replaced by a L\'evy process. We also suppose that the coefficient multiplying the increments of this process is merely Lipschitz…

Probability · Mathematics 2007-07-19 Benjamin Jourdain , Sylvie Méléard , Wojbor Woyczynski

Properties of systems driven by white non-Gaussian noises can be very different from these systems driven by the white Gaussian noise. We investigate stationary probability densities for systems driven by $\alpha$-stable L\'evy type noises,…

Statistical Mechanics · Physics 2009-11-13 B. Dybiec , E. Gudowska-Nowak , I. M. Sokolov

Recently, extracting data-driven governing laws of dynamical systems through deep learning frameworks has gained a lot of attention in various fields. Moreover, a growing amount of research work tends to transfer deterministic dynamical…

Machine Learning · Statistics 2022-07-05 Cheng Fang , Yubin Lu , Ting Gao , Jinqiao Duan
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