Results 11 to 20 of about 327,410 (288)
Strong Law of Large Numbers for Solutions of Non-Autonomous Stochastic Differential Equations
Наукові вісті Національного технічного університету України "Київський політехнічний інститут", 2017 Background. Asymptotic behavior at infinity of non-autonomous stochastic differential equation solutions is studied in the paper. Objective. The aim of the work is to find sufficient conditions for the strong law of large numbers for a random process ...
Oleg I. Klesov +2 more
doaj +1 more source
Efficient Memristive Stochastic Differential Equation Solver
Advanced Intelligent Systems, 2023 Herein, an efficient numerical solver for stochastic differential equations based on memristors is presented. The solver utilizes the stochastic switching effect in memristive devices to simulate the generation of a Brownian path and employs iterative ...
Xuening Dong +4 more
doaj +1 more source
Probabilistic Representations of Solutions of the Forward Equations [PDF]
, 2007 In this paper we prove a stochastic representation for solutions of the evolution equation $ \partial_t \psi_t = {1/2}L^*\psi_t $ where $ L^* $ is the formal adjoint of an elliptic second order differential operator with smooth coefficients corresponding
Rajeev, B., Thangavelu, S.
core +2 more sources
Stochastic model of innovation diffusion that takes into account the changes in the total market volume [PDF]
Известия Саратовского университета. Новая серия: Математика. Механика. Информатика, 2022 The article proposes a stochastic mathematical model of the diffusion of consumer innovations, which takes into account changes over time in the total number of potential buyers of an innovative product.
Parphenova, Alena Yu., Saraev, Leonid A.
doaj +1 more source
L2-convergence of Yosida approximation for semi-linear backward stochastic differential equation with jumps in infinite dimension [PDF]
Arab Journal of Mathematical SciencesPurpose – The main motivation of this paper is to present the Yosida approximation of a semi-linear backward stochastic differential equation in infinite dimension. Under suitable assumption and condition, an L2-convergence rate is established.
Hani Abidi +3 more
doaj +1 more source
Large deviations for stochastic Kuramoto–Sivashinsky equation with multiplicative noise
Nonlinear Analysis, 2021 The Kuramoto–Sivashinsky equation is a nonlinear parabolic partial differential equation, which describes the instability and turbulence of waves in chemical reactions and laminar flames. The aim of this work is to prove the large deviation principle for
Gregory Amali Paul Rose +2 more
doaj +1 more source
A kind of non-zero sum mixed differential game of backward stochastic differential equation
Advances in Difference Equations, 2020 This paper is concerned with a non-zero sum mixed differential game problem described by a backward stochastic differential equation. Here the term “mixed” means that this game problem contains a deterministic control v1 $v_{1}$ of Player 1 and a random ...
Huanjun Zhang
doaj +1 more source
Identification and estimation of continuous time dynamic systems with exogenous variables using panel data [PDF]
, 1993 This paper deals with the identification and maximum likelihood estimation of the parameters of a stochastic differential equation from discrete time sampling. Score function and maximum likelihood equations are derived explicitly.
Hamerle, Alfred +2 more
core +1 more source
SoftwareX, 2018 Stochastic simulations commonly require random process generation with a predefined probability density function (PDF) and an exponential autocorrelation function (ACF).
D. Bykhovsky
doaj +1 more source
Partial Differential Equations in Applied Mathematics, 2022 Backward stochastic differential equation solver was first introduced by Han et al in 2017. A semilinear parabolic partial differential equation is converted into a stochastic differential equation, and then solved by the backward stochastic differential
Evan Davis +4 more
doaj +1 more source