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This paper presents the error analysis of numerical methods on graded meshes for stochastic Volterra equations with weakly singular kernels. We first prove a novel regularity estimate for the exact solution via analyzing the associated…

Numerical Analysis · Mathematics 2023-09-01 Xinjie Dai , Jialin Hong , Derui Sheng

Sequential quadratic optimization algorithms are proposed for solving smooth nonlinear optimization problems with equality constraints. The main focus is an algorithm proposed for the case when the constraint functions are deterministic,…

Optimization and Control · Mathematics 2020-07-22 Albert Berahas , Frank E. Curtis , Daniel P. Robinson , Baoyu Zhou

We consider convolution-type stochastic Volterra equations with additive Hilbert-valued fractional Brownian motion, $0<H<1$. We find the weak solution to this stochastic Volterra equation, and study its stochastic integral part, the…

Probability · Mathematics 2007-05-23 Peter Caithamer , Anna Karczewska

This study aims to discuss the existence and uniqueness of solution of fuzzy Volterra integral equation with piecewise continuous kernel. Such problems appears in many balance problems for hereditary dynamic systems, e.g. in electric load…

General Mathematics · Mathematics 2024-01-18 Samad Noeiaghdam , Aliona I. Dreglea , Denis N. Sidorov

In this paper, we present a collocation method for nonlinear Volterra integral equation of the first kind. This method benefits from the idea of $hp$-version projection methods. We provide an approximation based on the Legendre polynomial…

Numerical Analysis · Mathematics 2019-10-15 Khadijeh Nedaiasl , Raziyeh Dehbozorgi , Khosrow Maleknejad

A numerical approach for the approximation of inertial manifolds of stochastic evolutionary equations with multiplicative noise is presented and illustrated. After splitting the stochastic evolutionary equations into a backward and a…

Dynamical Systems · Mathematics 2012-06-22 Xingye Kan , Jinqiao Duan , Ioannis G. Kevrekidis , Anthony J. Roberts

This paper presents a stochastic block-coordinate proximal Newton method for minimizing the sum of a blockwise Lipschitz-continuously differentiable function and a separable nonsmooth convex function. At each iteration, the method randomly…

Optimization and Control · Mathematics 2026-03-25 Hong Zhu , Xun Qian

In this work, weakly corrected explicit, semi-implicit and implicit Milstein approximations are presented for the solution of nonlinear stochastic differential equations. The solution trajectories provided by the Milstein schemes are…

Numerical Analysis · Mathematics 2021-08-25 Tapas Tripura , Budhaditya Hazra , Souvik Chakraborty

We described a method to solve deterministic and stochastic Walras equilibrium models based on associating with the given problem a bifunction whose maxinf-points turn out to be equilibrium points. The numerical procedure relies on an…

Optimization and Control · Mathematics 2018-02-23 Julio Deride , Alejandro Jofré , Roger J-B Wets

Stochastic differential equations (SDEs) offer powerful and accessible mathematical models for capturing both deterministic and probabilistic aspects of dynamic behavior across a wide range of physical, financial, and social systems.…

Statistics Theory · Mathematics 2026-02-17 Paromita Banerjee , Anirban Mondal

We propose a new nonconforming finite element algorithm to approximate the solution to the elliptic problem involving the fractional Laplacian. We first derive an integral representation of the bilinear form corresponding to the variational…

Numerical Analysis · Mathematics 2018-12-20 Andrea Bonito , Wenyu Lei , Joseph E. Pasciak

In this work we consider a simple, approximate, tending toward exact, solution of the system of two usual Lotka-Volterra differential equations. Given solution is obtained by an iterative method. In any finite approximation order of this…

Quantitative Methods · Quantitative Biology 2007-05-23 Vladan Pankovic , Banjac Dejan , Rade Glavatovic , Milan Predojevic

We consider minimization of stochastic functionals that are compositions of a (potentially) non-smooth convex function $h$ and smooth function $c$ and, more generally, stochastic weakly-convex functionals. We develop a family of stochastic…

Optimization and Control · Mathematics 2018-09-25 John Duchi , Feng Ruan

Volterra functions were introduced at the beginning of the twentieth century as solutions of some integral equations of convolution type with logarithmic kernel. Since then, few authors have studied this family of functions and faced with…

Complex Variables · Mathematics 2016-10-06 Roberto Garrappa , Francesco Mainardi

Backward stochastic differential equations (BSDEs) belong nowadays to the most frequently studied equations in stochastic analysis and computational stochastics. In this paper we prove that Picard iterations of BSDEs with globally Lipschitz…

Probability · Mathematics 2022-10-05 Arzu Ahmadova , Nazim I. Mahmudov

A stochastic conjugate gradient method for approximation of a function is proposed. The proposed method avoids computing and storing the covariance matrix in the normal equations for the least squares solution. In addition, the method…

Numerical Analysis · Mathematics 2013-02-11 Hong Jiang , Paul Wilford

In this paper, we consider the Euler method for backward stochastic Volterra integral equations. First, we approximate the original equation by a family of backward stochastic equations (BSDEs, for short). Then we solve the BSDEs by the…

Numerical Analysis · Mathematics 2016-05-17 Yanqing Wang

The existence of continuous not necessarily bounded solutions of nonlinear functional Volterra integral inclusions in infinite dimensional setting is shown with the aid of the measure of nonequicontinuity. New abstract topological fixed…

Classical Analysis and ODEs · Mathematics 2020-05-25 Radosław Pietkun

The purpose of this paper is to establish the convergence in distribution of the normalized error in the Euler approximation scheme for stochastic Volterra equations driven by a standard Brownian motion, with a kernel of the form…

Probability · Mathematics 2022-04-18 David Nualart , Bhargobjyoti Saikia

Using lattice approximations of Euclidean space, we develop a way to approximate stable processes that are represented by stochastic integrals over Euclidean space. Via a stable version of the Lindeberg-Feller Theorem we show that the…

Probability · Mathematics 2013-02-19 Clément Dombry , Paul Jung