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Diffusion processes have been widely used for approximations in the queueing theory. There are different types of diffusion approximations. Among them, we are interested in those obtained through limits of a sequence of models which…

Probability · Mathematics 2015-01-20 Masakiyo Miyazawa

This paper aims to develop and analyze a numerical scheme for solving the backward problem of semilinear subdiffusion equations. We establish the existence, uniqueness, and conditional stability of the solution to the inverse problem by…

Numerical Analysis · Mathematics 2025-05-07 Xu Wu , Jiang Yang , Zhi Zhou

This article introduces the splitting method to systems responding to rough paths as external stimuli. The focus is on nonlinear partial differential equations with rough noise but we also cover rough differential equations. Applications to…

Probability · Mathematics 2010-08-04 Peter Friz , Harald Oberhauser

System of semilinear ordinary differential equation and fractional differential equation of distributed order is investigated and solved in a mild and classical sense. Such a system arises as a distributed derivative model of…

Functional Analysis · Mathematics 2009-09-28 Teodor M. Atanackovic , Ljubica Oparnica , Stevan Pilipovic

We propose an approximation of nonlinear renewal equations by means of ordinary differential equations. We consider the integrated state, which is absolutely continuous and satisfies a delay differential equation. By applying the…

Numerical Analysis · Mathematics 2021-03-23 Francesca Scarabel , Odo Diekmann , Rossana Vermiglio

The advection-diffusion and wave equations are the fundamental equations governing any physical law and therefore arise in many areas of physics and astrophysics. For complex problems and geometries, only numerical simulations can give…

Computational Physics · Physics 2014-01-08 J. Pétri

We study the well-posedness of a nonlinear reaction diffusion partial differential equation system on the half-line coupled with a stochastic dynamical boundary condition, a random system arising from the description of the chemical…

Probability · Mathematics 2025-05-12 Mario Maurelli , Daniela Morale , Stefania Ugolini

Dynamical systems theory provides powerful methods to extract effective macroscopic dynamics from complex systems with slow modes and fast modes. Here we derive and theoretically support a macroscopic, spatially discrete, model for a class…

Analysis of PDEs · Mathematics 2010-03-12 Wei Wang , A. J. Roberts

An approximation to the solution of a stochastic parabolic equation is constructed using the Galerkin approximation followed by the Wiener Chaos decomposition. The result is applied to the nonlinear filtering problem for the time…

Probability · Mathematics 2007-06-13 Sergey V. Lototsky

This paper deals with the case of using nonlinear diffusion filters to obtain piecewise constant images as a previous process for segmentation techniques. We first show an intrinsic formulation for the nonlinear diffusion equation to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-24 Javier Sanguino , Carlos Platero , Olga Velasco

We propose a new numerical scheme designed for a wide class of structured population models based on the idea of operator splitting and particle approximations. This scheme is related to the Escalator Boxcar Train (EBT) method commonly used…

Analysis of PDEs · Mathematics 2013-06-10 J. A. Carrillo , P. Gwiazda , A. Ulikowska

A growing body of literature has been leveraging techniques of machine learning (ML) to build novel approaches to approximating the solutions to partial differential equations. Noticeably absent from the literature is a systematic…

Numerical Analysis · Mathematics 2026-05-19 Jonah A. Reeger

Fractional nonlinear differential equations present an interplay between two common and important effective descriptions used to simplify high dimensional or more complicated theories: nonlinearity and fractional derivatives. These…

Statistical Mechanics · Physics 2016-12-05 U. Al Khawaja , M. Al-Refai , Lincoln D. Carr

In this paper we investigate how standard nonlinear programming algorithms can be used to solve constrained optimization problems in a distributed manner. The optimization setup consists of a set of agents interacting through a…

Optimization and Control · Mathematics 2017-07-18 Ion Matei , John S. Baras

Mathematical modeling of many physical processes such as diffusion, viscosity of fluids and combustion involves differential equations with small coefficients of higher derivatives. These may be small diffusion coefficients for modeling the…

Numerical Analysis · Mathematics 2010-02-16 Liudmila Rozanova

The macroscopic behavior of dissipative stochastic partial differential equations usually can be described by a finite dimensional system. This article proves that a macroscopic reduced model may be constructed for stochastic…

Mathematical Physics · Physics 2008-12-11 Wei Wang , A. J. Roberts

Similarity reductions and new exact solutions are obtained for a nonlinear diffusion equation. These are obtained by using the classical symmetry group and reducing the partial differential equation to various ordinary differential…

Analysis of PDEs · Mathematics 2015-06-26 Maria Luz Gandarias , P. Venero , José Ramírez-Labrador

In this paper we construct numerical schemes to approximate linear transport equations with slab geometry by diffusion equations. We treat both the case of pure diffusive scaling and the case where kinetic and diffusive scalings coexist.…

Numerical Analysis · Mathematics 2015-05-18 Qin Li , Jianfeng Lu , Weiran Sun

High-dimensional fractional reaction-diffusion equations have numerous applications in the fields of biology, chemistry, and physics, and exhibit a range of rich phenomena. While classical algorithms have an exponential complexity in the…

Quantum Physics · Physics 2026-01-21 Dong An , Konstantina Trivisa

This paper proposes and analyzes a novel clustering algorithm that combines graph-based diffusion geometry with techniques based on density and mode estimation. The proposed method is suitable for data generated from mixtures of…

Machine Learning · Statistics 2019-01-01 Mauro Maggioni , James M. Murphy