In this work, we aim to prove the strong convergence of the sequence generated by the modified inertial parallel viscosity-type algorithm for finding a common fixed point of a finite family of nonexpansive mappings under mild conditions in real Hilbert spaces. Moreover, we present the numerical experiments to solve linear systems and differential problems using Gauss–Seidel, weight Jacobi, and successive over relaxation methods. Furthermore, we provide our algorithm to show the efficiency and implementation of the LASSO problems in signal recovery. The novelty of our algorithm is that we show that the algorithm is efficient compared with the existing algorithms
AbstractBy using viscosity approximation methods for a finite family of nonexpansive mappings in Ban...
AbstractViscosity approximation methods for nonexpansive mappings are studied. Consider the iteratio...
In this paper, by using generalized viscosity mappings, we prove two strong convergence theorems for...
Abstract For finding a common fixed point of a finite family of G-nonexpansive mappings, we implemen...
AbstractThe aim of this work is to propose implicit and explicit viscosity-like methods for finding ...
In this paper, strong convergence results for α−inverse strongly monotone operators under new algori...
In a real Hilbert space, an iterative scheme is considered to obtain a common fixed point for a coun...
AbstractThis paper deals with a general fixed point iteration for computing a point in some nonempty...
Abstract The purpose of this paper is to introduce and study the general viscosity approximation met...
AbstractIn this paper, we discuss the strong convergence of the viscosity approximation method, in H...
Many authors have proposed fixed-point algorithms for obtaining a fixed point of G-nonexpansive mapp...
We introduce a new composite iterative scheme by the viscosity approximation method for nonexpansiv...
Abstract The aim of this paper is to introduce a viscosity iterative algorithm for the implicit midp...
summary:In this paper, we study the strong convergence of the proximal gradient algorithm with inert...
Abstract In this article, we investigate the bounded perturbation resilience of the viscosity algori...
AbstractBy using viscosity approximation methods for a finite family of nonexpansive mappings in Ban...
AbstractViscosity approximation methods for nonexpansive mappings are studied. Consider the iteratio...
In this paper, by using generalized viscosity mappings, we prove two strong convergence theorems for...
Abstract For finding a common fixed point of a finite family of G-nonexpansive mappings, we implemen...
AbstractThe aim of this work is to propose implicit and explicit viscosity-like methods for finding ...
In this paper, strong convergence results for α−inverse strongly monotone operators under new algori...
In a real Hilbert space, an iterative scheme is considered to obtain a common fixed point for a coun...
AbstractThis paper deals with a general fixed point iteration for computing a point in some nonempty...
Abstract The purpose of this paper is to introduce and study the general viscosity approximation met...
AbstractIn this paper, we discuss the strong convergence of the viscosity approximation method, in H...
Many authors have proposed fixed-point algorithms for obtaining a fixed point of G-nonexpansive mapp...
We introduce a new composite iterative scheme by the viscosity approximation method for nonexpansiv...
Abstract The aim of this paper is to introduce a viscosity iterative algorithm for the implicit midp...
summary:In this paper, we study the strong convergence of the proximal gradient algorithm with inert...
Abstract In this article, we investigate the bounded perturbation resilience of the viscosity algori...
AbstractBy using viscosity approximation methods for a finite family of nonexpansive mappings in Ban...
AbstractViscosity approximation methods for nonexpansive mappings are studied. Consider the iteratio...
In this paper, by using generalized viscosity mappings, we prove two strong convergence theorems for...