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In this paper, we introduce a new three-step iteration process in Banach space and prove convergence results for approximating fixed points for nonexpansive mappings. Also, we show that the newly introduced iteration process converges…

Functional Analysis · Mathematics 2018-09-12 Chanchal Garodia , Izhar Uddin

The split common fixed-point problem is an inverse problem that consists in finding an element in a fixed-point set such that its image under a bounded linear operator belongs to another fixed-point set. Recently Censor and Segal proposed…

Optimization and Control · Mathematics 2014-11-03 Huanhuan Cui , Fenghui Wang

In this paper, we consider the problem of solving a constrained system of nonlinear equations. We propose an algorithm based on a combination of the Newton and conditional gradient methods, and establish its local convergence analysis. Our…

Optimization and Control · Mathematics 2016-08-25 Max L. N. Goncalves , Jefferson G. Melo

Landweber-type methods are prominent for solving ill-posed inverse problems in Banach spaces and their convergence has been well-understood. However, how to derive their convergence rates remains a challenging open question. In this paper,…

Numerical Analysis · Mathematics 2024-11-15 Qinian Jin

We established a new eighth-order iterative method, consisting of three steps, for solving nonlinear equations. Per iteration the method requires four evaluations (three function evaluations and one evaluation of the first derivative).…

Numerical Analysis · Mathematics 2013-04-18 J. P. Jaiswal , Neha Choubey

In this article we develop convergence theory for a general class of adaptive approximation algorithms for abstract nonlinear operator equations on Banach spaces, and use the theory to obtain convergence results for practical adaptive…

Numerical Analysis · Mathematics 2010-01-12 Michael Holst , Gantumur Tsogtgerel , Yunrong Zhu

The article deals with iterative methods of solving linear operator equations $x = Bx + f$ and $Ax = f$ with self-adjoint operators in Hilbert space $X$ in critical case when $\rho(B) = 1$ and $0 \in {\rm Sp}\, A$. The main results are…

Functional Analysis · Mathematics 2014-12-04 O. V. Matysik , P. P. Zabreiko

In this paper we established a class of optimal fourth-order methods which is obtained by existing third-order method for solving nonlinear equations for simple roots by using weight functions. Some physical examples are given to illustrate…

Numerical Analysis · Mathematics 2013-07-30 J. P. Jaiswal

In this paper we present a systematic study of regular sequences of quasi-nonexpansive operators in Hilbert space. We are interested, in particular, in weakly, boundedly and linearly regular sequences of operators. We show that the type of…

Optimization and Control · Mathematics 2018-02-13 Andrzej Cegielski , Simeon Reich , Rafał Zalas

A version of the Dynamical Systems Gradient Method for solving ill-posed nonlinear monotone operator equations is studied in this paper. A discrepancy principle is proposed and justified. A numerical experiment was carried out with the new…

Numerical Analysis · Mathematics 2009-03-04 N. S. Hoang , A. G. Ramm

Gradient descent method, as one of the major methods in numerical optimization, is the key ingredient in many machine learning algorithms. As one of the most fundamental way to solve the optimization problems, it promises the function value…

Quantum Physics · Physics 2021-02-01 Keren Li , Shijie Wei , Feihao Zhang , Pan Gao , Zengrong Zhou , Tao Xin , Xiaoting Wang , Guilu Long

A wide variety of (fixed-point) iterative methods for the solution of nonlinear equations (in Hilbert spaces) exists. In many cases, such schemes can be interpreted as iterative local linearization methods, which, as will be shown, can be…

Numerical Analysis · Mathematics 2019-10-16 Pascal Heid , Thomas P. Wihler

Operator learning refers to the application of ideas from machine learning to approximate (typically nonlinear) operators mapping between Banach spaces of functions. Such operators often arise from physical models expressed in terms of…

Machine Learning · Computer Science 2024-02-27 Nikola B. Kovachki , Samuel Lanthaler , Andrew M. Stuart

In this paper, we propose an inexact Newton-like conditional gradient method for solving constrained systems of nonlinear equations. The local convergence of the new method as well as results on its rate are established by using a general…

Optimization and Control · Mathematics 2017-05-23 M. L. N. Goncalves , F. R. Oliveira

A review of the authors's results is given. Several methods are discussed for solving nonlinear equations $F(u)=f$, where $F$ is a monotone operator in a Hilbert space, and noisy data are given in place of the exact data. A discrepancy…

Numerical Analysis · Mathematics 2009-01-29 N. S. Hoang , A. G. Ramm

In this paper, we present a new iterative approximate method of solving boundary value problems. The idea is to compute approximate polynomial solutions in the Bernstein form using least squares approximation combined with some properties…

Numerical Analysis · Computer Science 2017-09-08 Przemysław Gospodarczyk , Paweł Woźny

Stable computational algorithms for the approximate solution of the Cauchy problem for nonstationary problems are based on implicit time approximations. Computational costs for boundary value problems for systems of coupled multidimensional…

Numerical Analysis · Mathematics 2024-03-28 P. N. Vabishchevich

In this paper we consider a fully third order nonlinear boundary value problem which is of great interest of many researchers. First we establish the existence, uniqueness of solution. Next, we propose simple iterative methods on both…

Numerical Analysis · Mathematics 2020-04-24 Dang Quang A , Dang Quang Long

This is the first in a series of papers which deal with the development of novel methods for solving a system of linear algebraic equations with a time complexity lower than existing algorithms. The NxN system of linear equations, Ax = b,…

Optimization and Control · Mathematics 2022-06-16 Vilas Patwardhan

We consider the method of quasi-solutions (also referred to as Ivanov regularization) for the regularization of linear ill-posed problems in non-reflexive Banach spaces. Using the equivalence to a metric projection onto the image of the…

Optimization and Control · Mathematics 2018-10-09 Christian Clason , Andrej Klassen
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