Solutions for Functional Fully Coupled Forward-Backward Stochastic Differential Equations [PDF]
, 2013 In this paper, we study a functional fully coupled forward-backward stochastic differential equations (FBSDEs). Under a new type of integral Lipschitz and monotonicity conditions, the existence and uniqueness of solutions for functional fully coupled ...
Ji, Shaolin, Yang, Shuzhen
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Linear stochastic differential equations with functional boundary conditions [PDF]
The Annals of Probability, 2003 25 ...
FERRANTE, MARCO, ALABERT A.
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Backward Stochastic Linear Quadratic Optimal Control with Expectational Equality Constraint
MathematicsThis paper investigates a backward stochastic linear quadratic control problem with an expected-type equality constraint on the initial state. By using the Lagrange multiplier method, the problem with a uniformly convex cost functional is first ...
Yanrong Lu, Jize Li, Yonghui Zhou
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Gradient Bounds for Solutions of Stochastic Differential Equations Driven by Fractional Brownian Motions [PDF]
, 2011 We study some functional inequalities satisfied by the distribution of the solution of a stochastic differential equation driven by fractional Brownian motions.
Cheng Ouyang +3 more
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Heat kernel regularization of the effective action for stochastic reaction-diffusion equations
, 2000 The presence of fluctuations and non-linear interactions can lead to scale dependence in the parameters appearing in stochastic differential equations. Stochastic dynamics can be formulated in terms of functional integrals.
A.A. Grib +37 more
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Schauder’s fixed-point theorem in approximate controllability problems
International Journal of Applied Mathematics and Computer Science, 2016 The main objective of this article is to present the state of the art concerning approximate controllability of dynamic systems in infinite-dimensional spaces.
Babiarz Artur +2 more
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Functional Approach to Stochastic Inflation
, 1994 We propose functional approach to the stochastic inflationary universe dynamics. It is based on path integral representation of the solution to the differential equation for the scalar field probability distribution.
A. D. Linde +8 more
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Extreme Analysis of a Non-convex and Nonlinear Functional of Gaussian Processes -- On the Tail Asymptotics of Random Ordinary Differential Equations [PDF]
, 2013 In this paper, we consider a stochastic system described by a differential equation admitting a spatially varying random coefficient. The differential equation has been employed to model various static physics systems such as elastic deformation, water
Liu, Jingchen, Zhou, Xiang
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Coarse-grained forms for equations describing the microscopic motion of particles in a fluid
, 2013 Equations of motion for the microscopic number density $\hat{\rho}({\bf x},t)$ and the momentum density $\hat{\bf g}({\bf x},t)$ of a fluid have been obtained in the past from the corresponding Langevin equations representing the dynamics of the fluid ...
Das, Shankar P., Yoshimori, Akira
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Stochastic Functional Differential Equations and Sensitivity to Their Initial Path [PDF]
, 2018 We consider systems with memory represented by stochastic functional differential equations. Substantially, these are stochastic differential equations with coefficients depending on the past history of the process itself. Such coefficients are hence defined on a functional space.
Baños, David +3 more
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