In this paper we consider thearithmetic mean method for solving large sparse systems of linear equations. This iterative method converges for systems with coefficient matrices that are symmetric positive definite or positive real or irreducible L-matrices with a strong diagonal dominance. The method is very suitable for parallel implementation on a multiprocessor system, such as the CRAY X-MP. Some numerical experiments on systems resulting from the discretization, by means of the usual 5-point difference formulae, of an elliptic partial differential equation are presented
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
In this thesis we consider the problems that arise in computational linear algebra when ...
AbstractIn this paper we consider thearithmetic mean method for solving large sparse systems of line...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...
AbstractA class of parallel decomposition-type accelerated over-relaxation methods, including four a...
In several recent works, the Arithmetic Mean Method for solving large sparse linear systems has been...
Introduction One of the fundamental task of numerical computing is the ability to solve linear syst...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
We propose a novel iterative algorithm for solving a large sparse linear system. The method is based...
In the second edition of this classic monograph, complete with four new chapters and updated referen...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...
AbstractIn this paper, we consider a new form of the arithmetic mean method for solving large block ...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
Many problems in applied mathematics can be formulated as a Sylvester matrix equation AX+XB=C. Itera...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
In this thesis we consider the problems that arise in computational linear algebra when ...
AbstractIn this paper we consider thearithmetic mean method for solving large sparse systems of line...
In this paper we consider the arithmetic mean method for solving large sparse systems of linear equa...
AbstractA class of parallel decomposition-type accelerated over-relaxation methods, including four a...
In several recent works, the Arithmetic Mean Method for solving large sparse linear systems has been...
Introduction One of the fundamental task of numerical computing is the ability to solve linear syst...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
We propose a novel iterative algorithm for solving a large sparse linear system. The method is based...
In the second edition of this classic monograph, complete with four new chapters and updated referen...
AbstractAn algorithm is presented for the general solution of a set of linear equations Ax=b. The me...
AbstractIn this paper, we consider a new form of the arithmetic mean method for solving large block ...
In this paper, we consider a new form of the arithmetic mean method for solving large block tridiago...
Many problems in applied mathematics can be formulated as a Sylvester matrix equation AX+XB=C. Itera...
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate...
We discuss a variety of iterative methods that are based on the Arnoldi process for solving large sp...
In this thesis we consider the problems that arise in computational linear algebra when ...