Results 11 to 20 of about 44,706 (312)

Maple for Stochastic Differential Equations [PDF]

, 2001
This paper introduces the MAPLE software package stochastic consisting of MAPLE routines for stochastic calculus and stochastic differential equations and for constructing basic numerical methods for specific stochastic differential equations, with simple examples illustrating the use of the routines.
Grüne, Lars, Kloeden, Peter E., Cyganowski, Sasha   +2 more
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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, Ilona I. Sirenka, Olena A. Tymoshenko   +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, Louis Primeau, Roman Genov, Mostafa Rahimi Azghadi, Amirali Amirsoleimani   +4 more
doaj   +1 more source

Triviality of the 2D stochastic Allen-Cahn equation [PDF]

, 2012
We consider the stochastic Allen-Cahn equation driven by mollified space-time white noise. We show that, as the mollifier is removed, the solutions converge weakly to 0, independently of the initial condition.
H. Weber, Martin Hairer, Hairer, Martin, Marc D. Ryser, M. Hairer, Hendrik Weber, Weber, Hendrik, M. D. Ryser, Ryser, Marc D.   +8 more
core   +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, Murugan Suvinthra, Krishnan Balachandran   +2 more
doaj   +1 more source

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

A stochastic differential equation SIS epidemic model [PDF]

, 2011
In this paper we extend the classical susceptible-infected-susceptible epidemic model from a deterministic framework to a stochastic one and formulate it as a stochastic differential equation (SDE) for the number of infectious individuals $I(t)$. We then
Hu, L., X. Mao, Greenhalgh, David, D. Greenhalgh, Mao, Xuerong, Gray, Alison, Pan, Jiafeng, A. Gray, L. Hu, J. Pan   +9 more
core   +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 Sciences
Purpose – 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, Rim Amami, Roger Pettersson, Chiraz Trabelsi   +3 more
doaj   +1 more source

Stochastic Differential Equations in a Differentiable Manifold [PDF]

Nagoya Mathematical Journal, 1950
The theory of stochastic differential equations in a differentiate manifold has been established by many authors from different view-points, especially by R Lévy [2], F. Perrin [1], A. Kolmogoroff [1] [2] and K. Yosida [1] [2]. It is the purpose of the present paper to discuss it by making use of stochastic integrals.
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Harmonic analysis of stochastic equations and backward stochastic differential equations [PDF]

Probability Theory and Related Fields, 2008
The BMO martingale theory is extensively used to study nonlinear multi-dimensional stochastic equations (SEs) in $\cR^p$ ($p\in [1, \infty)$) and backward stochastic differential equations (BSDEs) in $\cR^p\times \cH^p$ ($p\in (1, \infty)$) and in $\cR^\infty\times \bar{\cH^\infty}^{BMO}$, with the coefficients being allowed to be unbounded.
Delbaen, Freddy, Tang, Shanjian
openaire   +3 more sources