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Related papers: Stochastic bifurcation models

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Motivated by applications in queueing theory, we consider a class of singular stochastic control problems whose state space is the d-dimensional positive orthant. The original problem is approximated by a drift control problem, to which we…

Systems and Control · Electrical Eng. & Systems 2024-04-18 Baris Ata , J. Michael Harrison , Nian Si

In this paper we show that solutions of stochastic partial differential equations driven by Brownian motion can be approximated by stochastic partial differential equations forced by pure jump noise/random kicks. Applications to stochastic…

Probability · Mathematics 2014-01-31 Giulia Di Nunno , Tusheng Zhang

In this paper, a stochastic control problem under model uncertainty with general penalty term is studied. Two types of penalties are considered. The first one is of type f-divergence penalty treated in the general framework of a continuous…

Probability · Mathematics 2016-10-11 Wahid Faidi , Anis Matoussi , Mohamed Mnif

We consider a generic and explicit tamed Euler--Maruyama scheme for multidimensional time-inhomogeneous stochastic differential equations with multiplicative Brownian noise. The diffusive coefficient is uniformly elliptic, H\"older…

Probability · Mathematics 2025-02-03 Khoa Lê , Chengcheng Ling

In this article, we present a general methodology for control problems driven by the Brownian motion filtration including non-Markovian and non-semimartingale state processes controlled by mutually singular measures. The main result of this…

Probability · Mathematics 2018-01-19 Dorival Leão , Alberto Ohashi , Francys Souza

We present a theory of backward stochastic differential equations in continuous time with an arbitrary filtered probability space. No assumptions are made regarding the left continuity of the filtration, of the predictable quadratic…

Probability · Mathematics 2012-10-15 Samuel N. Cohen , Robert J. Elliott

The theory of one-dimensional stochastic differential equations driven by Brownian motion is classical and has been largely understood for several decades. For stochastic differential equations with jumps the picture is still incomplete,…

Probability · Mathematics 2020-12-15 Sam Baguley , Leif Doering , Andreas Kyprianou

Transport phenomena are ubiquitous in nature and known to be important for various scientific domains. Examples can be found in physics, electrochemistry, heterogeneous catalysis, physiology, etc. To obtain new information about diffusive…

Probability · Mathematics 2007-05-23 Denis S. Grebenkov

We consider a d-dimensional stochastic differential equation with additive noise and a drift coefficient which is assumed only to be a bounded Borel function. We show that, for almost all choices of the driving Brownian path, the equation…

Probability · Mathematics 2007-09-27 A. M. Davie

We consider a stochastic boundary value elliptic problem on a bounded domain $D\subset \mathbb{R}^k$, driven by a fractional Brownian field with Hurst parameter $H=(H_1,...,H_k)\in[{1/2},1[^k$. First we define the stochastic convolution…

Probability · Mathematics 2009-05-06 Marta Sanz-Solé , Iván Torrecilla

Lanchester's model of combat has certain deficiencies in its standard form arising from the neglect of the influence of random fluctuations. Several approaches to rectify this have been proposed and various results are scattered throughout…

Physics and Society · Physics 2019-05-09 Michael J. Kearney , Richard J. Martin

Uncertainties are abundant in complex systems. Mathematical models for these systems thus contain random effects or noises. The models are often in the form of stochastic differential equations, with some parameters to be determined by…

Numerical Analysis · Mathematics 2015-03-13 Jiarui Yang , Jinqiao Duan

Bifurcation analysis has many applications in different scientific fields, such as electronics, biology, ecology, and economics. In population biology, deterministic methods of bifurcation are commonly used. In contrast, stochastic…

Dynamical Systems · Mathematics 2021-10-27 Almaz Tesfay , Daniel Tesfay , Shenglan Yuan , James Brannan , Jinqiao Duan

We investigate the existence and uniqueness of non-Markovian second-order backward stochastic differential equations with an uncertain terminal horizon and establish comparison principles under the assumption that the driver is Lipschitz…

Probability · Mathematics 2025-06-19 Alberto Gennaro , Thibaut Mastrolia

We investigate piecewise-linear stochastic models as with regards to the probability distribution of functionals of the stochastic processes, a question which occurs frequently in large deviation theory. The functionals that we are looking…

Statistical Mechanics · Physics 2015-06-22 Yaming Chen , Wolfram Just

We investigate pathwise turnpike behavior of discrete-time stochastic linear-quadratic optimal control problems. Our analysis is based on a novel strict dissipativity notion for such problems, in which a stationary stochastic process…

Optimization and Control · Mathematics 2024-03-25 Jonas Schießl , Ruchuan Ou , Timm Faulwasser , Michael Heinrich Baumann , Lars Grüne

The stochastic Cahn-Hilliard equation driven by a fractional Brownian sheet provides a more accurate model for correlated space-time random perturbations. This study delves into two key aspects: first, it rigorously examines the regularity…

Numerical Analysis · Mathematics 2026-02-16 Nan Deng , Wanrong Cao

We discuss the identification of a time-dependent potential in a time-fractional diffusion model from a boundary measurement taken at a single point. Theoretically, we establish a conditional Lipschitz stability for this inverse problem.…

Numerical Analysis · Mathematics 2024-07-23 Siyu Cen , Kwancheol Shin , Zhi Zhou

Motivated by studies of indirect measurements in quantum mechanics, we investigate stochastic differential equations with a fixed point subject to an additional infinitesimal repulsive perturbation. We conjecture, and prove for an important…

Mathematical Physics · Physics 2018-07-18 Michel Bauer , Denis Bernard

In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idealized model of a diffusion where approximations such as…

Optimization and Control · Mathematics 2023-12-07 Somnath Pradhan , Zachary Selk , Serdar Yüksel