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We introduce a new numerical algorithm for solving the stochastic neural field equation (NFE) with delays. Using this algorithm we have obtained some numerical results which illustrate the effect of noise in the dynamical behaviour of…

Numerical Analysis · Mathematics 2017-01-17 Pedro M. Lima , Evelyn Buckwar

Stochastic averaging for a class of backward stochastic differential equations driven by both standard and fractional Brownian motions (SFrBSDEs in short), is investigated. An averaged SFrBSDEs for the original SFrBSDEs is proposed, and…

Probability · Mathematics 2021-06-04 Ibrahima Faye , Sadibou Aidara , Yaya Sagna

This paper studies explicit numerical approximations of the invariant probability measures (IPMs) for stochastic functional differential equations (SFDEs) with infinite delay under one-sided Lipschitz condition on the drift coefficient. To…

Numerical Analysis · Mathematics 2026-03-06 Guozhen Li , Shan Huang , Xiaoyue Li , Xuerong Mao

In this work, we present a general technique for establishing the strong convergence of numerical methods for stochastic delay differential equations (SDDEs) in the infinite horizon. This technique can also be extended to analyze certain…

Numerical Analysis · Mathematics 2025-05-21 Yudong Wang , Hongjiong Tian

This tutorial teaches parts of the finite element method (FEM), and solves a stochastic partial differential equation (SPDE). The contents herein are considered "known" in the numerics literature, but for statisticians it is very difficult…

Computation · Statistics 2022-02-15 Haakon Bakka

We present a numerical method for the approximation of solutions for the class of stochastic differential equations driven by Brownian motions which induce stochastic variation in fixed directions. This class of equations arises naturally…

Numerical Analysis · Mathematics 2010-06-15 David F. Anderson , Jonathan C. Mattingly

Speculative Decoding (SD) enforces strict distributional equivalence to the target model when accepting candidate tokens. While it maintains the target model's generation quality, this strict equivalence limits the speedup achievable by SD…

Artificial Intelligence · Computer Science 2025-06-04 Maximilian Holsman , Yukun Huang , Bhuwan Dhingra

In this paper we study solutions to stochastic differential equations (SDEs) with discontinuous drift. We apply two approaches: The Euler-Maruyama method and the Fokker-Planck equation and show that a candidate density function based on the…

Systems and Control · Computer Science 2013-08-27 Maria Simonsen , John Leth , Henrik Schioler , Horia Cornean

In this paper numerical methods for solving stochastic differential equations with Markovian switching (SDEwMSs) are developed by pathwise approximation. The proposed family of strong predictor-corrector Euler-Maruyama methods is designed…

Numerical Analysis · Mathematics 2011-03-08 Jun Ye , Haibo Li , Lili Xiao

A method for the numerical solution of variable order (VO) fractional differential equations (FDE) is presented. The method applies to linear as well as to nonlinear VO-FDEs. The Caputo type VO fractional derivative is employed. First, an…

Numerical Analysis · Mathematics 2018-05-08 John T. Katsikadelis

A novel efficient and high accuracy numerical method for the time-fractional differential equations (TFDEs) is proposed in this work. We show the equivalence between TFDEs and the integer-order extended parametric differential equations…

Numerical Analysis · Mathematics 2025-05-13 Peng Ding , Zhiping Mao

The primary goal of this research is to propose a novel architecture for a deep neural network that can solve fractional differential equations accurately. A Gaussian integration rule and a $L_1$ discretization technique are used in the…

Machine Learning · Computer Science 2023-09-15 Ali Nosrati Firoozsalari , Hassan Dana Mazraeh , Alireza Afzal Aghaei , Kourosh Parand

The intrusive (sample-free) spectral stochastic finite element method (SSFEM) is a powerful numerical tool for solving stochastic partial differential equations (PDEs). However, it is not widely adopted in academic and industrial…

Numerical Analysis · Mathematics 2022-09-20 Ajit Desai

In this article, we introduce a differentiability concept for fuzzy functions $\tilde{f}: F(\mathbb{R}) \to F(\mathbb{R})$, where $F(\mathbb{R})$ is the set of all fuzzy numbers. With the help of the proposed differentiability notion, we…

Optimization and Control · Mathematics 2019-10-08 U. M. Pirzada , Debdas Ghosh

Construction of splitting-step methods and properties of related non-negativity and boundary preserving numerical algorithms for solving stochastic differential equations (SDEs) of Ito-type are discussed. We present convergence proofs for a…

Numerical Analysis · Mathematics 2007-05-23 Esteban Moro , Henri Schurz

In this paper, we investigate the problem of strong approximation of the solutions of stochastic differential equations (SDEs) when the drift coefficient is given in integral form. We investigate its upper error bounds, in terms of the…

Numerical Analysis · Mathematics 2025-11-20 Paweł Przybyłowicz , Michał Sobieraj

This paper deals with uncertain dynamical systems in which predictions about the future state of a system are assessed by so called pseudomeasures. Two special cases are stochastic dynamical systems, where the pseudomeasure is the…

chao-dyn · Physics 2016-08-31 Andreas Hamm

Multi-variable nonlinear fuzzy optimization problem is considered under linear order relation on fuzzy numbers. Using gH-differentiability of a fuzzy-valued function $\tilde{f}$, new necessary and sufficient optimality conditions are…

General Mathematics · Mathematics 2018-02-28 Umme Salma M. Pirzada

A new method for solving numerically stochastic partial differential equations (SPDEs) with multiple scales is presented. The method combines a spectral method with the heterogeneous multiscale method (HMM) presented in [W. E, D. Liu, and…

Numerical Analysis · Mathematics 2015-05-28 A. Abdulle , G. A. Pavliotis

The paper presents a general strategy to solve ordinary differential equations (ODE), where some coefficient depend on the spatial variable and on additional random variables. The approach is based on the application of a recently developed…

Numerical Analysis · Mathematics 2019-07-17 Maximilian Bochmann , Lutz Kämmerer , Daniel Potts