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We develop a notion of nonlinear expectation --G-expectation-- generated by a nonlinear heat equation with infinitesimal generator G. We first study multi-dimensional G-normal distributions. With this nonlinear distribution we can introduce…

Probability · Mathematics 2007-05-23 Shige Peng

In this paper, we prove a convergence theorem for singular perturbations problems for a class of fully nonlinear parabolic partial differential equations with ergodic structures. The limit function is represented as the viscosity solution…

Probability · Mathematics 2021-07-19 Mingshang Hu , Falei Wang

The G-Brownian-motion-driven stochastic differential equations (G-SDEs) as well as the G-expectation, which were seminally proposed by Peng and his colleagues, have been extensively applied to describing a particular kind of uncertainty…

Probability · Mathematics 2025-01-08 Xiaoxiao Peng , Shijie Zhou , Wei Lin , Xuerong Mao

We introduce a notion of nonlinear expectation --G--expectation-- generated by a nonlinear heat equation with infinitesimal generator G. We first discuss the notion of G-standard normal distribution. With this nonlinear distribution we can…

Probability · Mathematics 2007-05-23 Shige Peng

The present paper considers a new kind of backward stochastic differential equations driven by G-Brownian motion, which is called ergodic G-BSDEs. Firstly, the well-posedness of G-BSDEs with infinite horizon is given by a new linearization…

Probability · Mathematics 2017-01-13 Mingshang Hu , Falei Wang

Path-dependent PDEs (PPDEs) are natural objects to study when one deals with non Markovian models. Recently, after the introduction of the so-called pathwise (or functional or Dupire) calculus (see [15]), in the case of finite-dimensional…

Probability · Mathematics 2017-03-07 Andrea Cosso , Salvatore Federico , Fausto Gozzi , Mauro Rosestolato , Nizar Touzi

We study a statistical model for infinite dimensional Gaussian random variables with unknown parameters. For this model we derive linear estimators for the mean and the variance of the Gaussian distribution. Furthermore, we construct…

Statistics Theory · Mathematics 2025-11-21 Stefan Tappe

We propose notions of minimax and viscosity solutions for a class of fully nonlinear path-dependent PDEs with nonlinear, monotone, and coercive operators on Hilbert space. Our main result is well-posedness (existence, uniqueness, and…

Analysis of PDEs · Mathematics 2018-07-24 Erhan Bayraktar , Christian Keller

In this paper, we consider the stochastic optimal control problems under G-expectation. Based on the theory of backward stochastic differential equations driven by G-Brownian motion, which was introduced in [10.11], we can investigate the…

Probability · Mathematics 2013-08-19 Zhonghao Zheng , Xiuchun Bi , Shuguang Zhang

We consider a one dimensional transport model with nonlocal velocity given by the Hilbert transform and develop a global well-posedness theory of probability measure solutions. Both the viscous and non-viscous cases are analyzed. Both in…

Analysis of PDEs · Mathematics 2011-11-01 J. A. Carrillo , L. C. F. Ferreira , J. C. Precioso

In this paper, we study the well-posedness of multi-dimensional backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) with diagonal generators, the $z$ parts of whose $l$-th components only depend on the…

Probability · Mathematics 2020-02-18 Guomin Liu

We establish necessary and sufficient conditions for stochastic invariance of closed subsets in Hilbert spaces for solutions to infinite-dimensional stochastic differential equations (SDEs) under mild assumptions on the coefficients. Our…

Probability · Mathematics 2026-02-24 Eduardo Abi Jaber , Stefan Tappe

We introduce a new notion of G-expectation-weighted Sobolev spaces, or in short, G-Sobolev spaces, and prove that a backward SDEs driven by G-Brownian motion are in fact path dependent PDEs in the corresponding Sobolev spaces under G-norms.…

Probability · Mathematics 2014-03-19 Shige Peng , Yongsheng Song

In this paper, we obtain the existence and uniqueness theorem for backward stochastic differential equation driven by G-Brownian motion (G-BSDE) under degenerate case. Moreover, we propose a new probabilistic method based on the…

Probability · Mathematics 2022-05-20 Mingshang Hu , Shaolin Ji , Xiaojuan Li

In this paper we study the problems of invariant and ergodic measures under G-expectation framework. In particular, the stochastic differential equations driven by G-Brownian motion have the unique invariant and ergodic measures. Moreover,…

Probability · Mathematics 2014-09-12 Mingshang Hu , Hanwu Li , Falei Wang , Guoqiang Zheng

This paper first studies super linear G-expectation. Uniqueness and existence theorem for backward stochastic differential equations (BSDEs) under super linear expectation is established to provide probabilistic interpretation for the…

Probability · Mathematics 2010-09-07 Yuhong Xu

We define $g$-expectation of a distribution as the infimum of the $g$-expectations of all the terminal random variables sharing that distribution. We present two special cases for nonlinear $g$ where the $g$-expectation of distributions can…

Probability · Mathematics 2022-08-16 Mingyu Xu , Zuo Quan Xu , Xun Yu Zhou

These notes rigorously construct the stochastic integral of a Hilbert Space valued process driven by a Cylindrical Brownian Motion. We expand upon this stochastic calculus to present an introduction to stochastic differential equations in…

Probability · Mathematics 2023-09-15 Daniel Goodair

We introduce a second-order stochastic model to explore the variability in growth of biological shapes with applications to medical imaging. Our model is a perturbation with a random force of the Hamiltonian formulation of the geodesics.…

Probability · Mathematics 2010-03-23 François-Xavier Vialard

We introduce a new notion of G-normal distributions. This will bring us to a new framework of stochastic calculus of Ito's type (Ito's integral, Ito's formula, Ito's equation) through the corresponding G-Brownian motion. We will also…

Probability · Mathematics 2007-11-20 Shige Peng
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