On modification of certain methods of the conjugate direction type for solving systems of linear algebraic equations

A modification of certain well-known methods of the conjugate direction type is proposed and examined. The modified methods are more stable with respect to the accumulation of round-off errors. Moreover, these methods are applicable for solving ill-conditioned systems of linear algebraic equations that, in particular, arise as approximations of ill-posed problems. Numerical results illustrating the advantages of the proposed modification are presented.     

A modification of conjugate direction methods

A modification of well-known conjugate direction methods is proposed and examined. The modified methods are more stable with respect to round-off error accumulation and are applicable to ill-conditioned and ill-posed problems. The advantages of the modification are illustrated by numerical experiments.     

On a modification of minimal iteration methods for solving systems of linear algebraic equations

Modifications of certain minimal iteration methods for solving systems of linear algebraic equations are proposed and examined. The modified methods are shown to be superior to the original versions with respect to the round-off error accumulation, which makes them applicable to solving ill-conditioned problems. Numerical results demonstrating the efficiency of the proposed modifications are given.     

On solving equations of algebraic sum of equal powers

It is well known that a system of equations of sum of equal powers can be converted to an algebraic equation of higher degree via Newton's identities. This is the Viete-Newton theorem. This work reports the generalizations of the Viete-Newton theorem to a system of equations of algebraic sum of equal powers. By exploiting some facts from algebra and combinatorics, it is shown that a system of equations of algebraic sum of equal powers can be converted in a closed form to two algebraic equations, whose degree sum equals the number of unknowns of the system of equations of algebraic sum of equal powers.     

An exponential matrix method for solving systems of linear differential equations

This paper presents an exponential matrix method for the solutions of systems of high‐order linear differential equations with variable coefficients. The problem is considered with the mixed conditions. On the basis of the method, the matrix forms of exponential functions and their derivatives are constructed, and then by substituting the collocation points into the matrix forms, the fundamental matrix equation is formed. This matrix equation corresponds to a system of linear algebraic equations. By solving this system, the unknown coefficients are determined and thus the approximate solutions are obtained. Also, an error estimation based on the residual functions is presented for the method. The approximate solutions are improved by using this error estimation. To demonstrate the efficiency of the method, some numerical examples are given and the comparisons are made with the results of other methods. Copyright © 2012 John Wiley & Sons, Ltd.     

Superlinear convergence theorem in the ABSg class of algorithms for nonlinear algebraic equations

In this paper, it is shown that, when two subclasses of algorithms in the ABSg family are applied to a set of nonlinear algebraic equations, then the convergence is superlinear. The conditions for the theorem to be true are essentially the same as those that apply to the Newton method.This work was undertaken while the author was at Hatfield Polytechnic working under SERC Grant No. GR/E 07760.     

On relaxed greedy randomized Kaczmarz methods for solving large sparse linear systems

For solving large sparse systems of linear equations by iteration methods, we further generalize the greedy randomized Kaczmarz method by introducing a relaxation parameter in the involved probability criterion, obtaining a class of relaxed greedy randomized Kaczmarz methods. We prove the convergence of these methods when the linear system is consistent, and show that these methods can be more efficient than the greedy randomized Kaczmarz method if the relaxation parameter is chosen appropriately.     

Multiquadric quasi‐interpolation methods for solving partial differential algebraic equations

In this article, we propose two meshless collocation approaches for solving time dependent partial differential algebraic equations (PDAEs) in terms of the multiquadric quasi‐interpolation schemes. In presenting the process of the solution, the error is estimated. Furthermore, the comparisons on condition numbers of the collocation matrices using different methods and the sensitivity of the shape parameter c are given. With the use of the appropriate collocation points, the method for PDAEs with index‐2 is improved. The results show that the methods have some advantages over some known methods, such as the smaller condition numbers or more accurate solutions for PDAEs which has an modal index‐2 or an impulse solution with index‐2. Copyright © 2012 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 30: 95–119, 2014     

Conjugate direction methods for solving systems of linear equations

A generalization of the notion of a set of directions conjugate to a matrix is shown to lead to a variety of finitely terminating iterations for solving systems of linear equations. The errors in the iterates are characterized in terms of projectors constructable from the conjugate directions. The natural relations of the algorithms to well known matrix decompositions are pointed out. Some of the algorithms can be used to solve linear least squares problems.This work was supported by the Office of Naval Research under contract number N 00014-67-A-0126.     

A stopping criterion for the iterative solution of an overdetermined system of linear algebraic equations

For an overdetermined system of linear algebraic equations, systems obtained by introducing independent random errors into the original right-hand side are examined. Under certain assumptions on how these random variables are distributed, a practical stopping criterion is proposed for an iterative process that minimizes the sum of the squares of the residuals for the above systems. Numerical results demonstrating the efficiency of this criterion for some ill-conditioned problems are presented.     

Analysis of reaction-diffusion systems by the method of linear determining equations

Exact solutions to two-component systems of reaction-diffusion equations are sought by the method of linear determining equations (LDEs) generalizing the methods of the classical group analysis of differential equations. LDEs are constructed for a system of two second-order evolutionary equations. The results of solving the LDEs are presented for two-component systems of reaction-diffusion equations with polynomial nonlinearities in the diffusion coefficients. Examples of constructing noninvariant solutions are presented for the reaction-diffusion systems that possess invariant manifolds.     

ABS methods and ABSPACK for linear systems and optimization: A review

ABS methods are a large class of methods, based upon the Egervary rank reducing algebraic process, first introduced in 1984 by Abaffy, Broyden and Spedicato for solving linear algebraic systems, and later extended to nonlinear algebraic equations, to optimization problems and other fields; software based upon ABS methods is now under development. Current ABS literature consists of about 400 papers. ABS methods provide a unification of several classes of classical algorithms and more efficient new solvers for a number of problems. In this paper we review ABS methods for linear systems and optimization, from both the point of view of theory and the numerical performance of ABSPACK.Work partially supported by ex MURST 60% 2001 funds.E. Spedicato     

The use of second degree normalized implicit conjugate gradient methods for solving large sparse systems of linear equations

Second degree normalized implicit conjugate gradient methods for the numerical solution of self-adjoint elliptic partial differential equations are developed. A proposal for the selection of certain values of the iteration parameters ?_i, γ_i involved in solving two and three-dimensional elliptic boundary-value problems leading to substantial savings in computational work is presented. Experimental results for model problems are given.     

Two composition methods for solving certain systems of linear equations

Summary This note is concerned with the following problem: Given a systemA·x=b of linear equations and knowing that certains of its subsystemsA ¹·x ¹=b ¹, ...,A ^m ·x ^m =b ^m can be solved uniquely what can be said about the regularity ofA and how to find the solutionx fromx ¹, ...,x ^m ? This question is of particular interest for establishing methods computing certain linear or quasilinear sequence transformations recursively [7, 13, 15].Work performed under NATO Research Grant 027-81     

Multistep methods for differential algebraic equations

Multistep methods for the differential/algebraic equations (DAEs) in the form of

On the convergence of inexact Newton methods for discrete-time algebraic Riccati equations

In this paper, we present a convergence analysis of the inexact Newton method for solving Discrete-time algebraic Riccati equations (DAREs) for large and sparse systems. The inexact Newton method requires, at each iteration, the solution of a symmetric Stein matrix equation. These linear matrix equations are solved approximatively by the alternating directions implicit (ADI) or Smith?s methods. We give some new matrix identities that will allow us to derive new theoretical convergence results for the obtained inexact Newton sequences. We show that under some necessary conditions the approximate solutions satisfy some desired properties such as the d-stability. The theoretical results developed in this paper are an extension to the discrete case of the analysis performed by Feitzinger et al. (2009) [8] for the continuous-time algebraic Riccati equations. In the last section, we give some numerical experiments.     

An efficient multistep iteration scheme for systems of nonlinear algebraic equations associated with integral equations

The aim of this research is to present a new iterative procedure in approximating nonlinear system of algebraic equations with applications in integral equations as well as partial differential equations (PDEs). The presented scheme consists of several steps to reach a high rate of convergence and also an improved index of efficiency. The theoretical parts are furnished, and several computational tests mainly arising from practical problems are given to manifest its applicability.     

A two-step matrix splitting iteration paradigm based on one single splitting for solving systems of linear equations

For solving large sparse systems of linear equations, we construct a paradigm of two-step matrix splitting iteration methods and analyze its convergence property for the nonsingular and the positive-definite matrix class. This two-step matrix splitting iteration paradigm adopts only one single splitting of the coefficient matrix, together with several arbitrary iteration parameters. Hence, it can be constructed easily in actual applications, and can also recover a number of representatives of the existing two-step matrix splitting iteration methods. This result provides systematic treatment for the two-step matrix splitting iteration methods, establishes rigorous theory for their asymptotic convergence, and enriches algorithmic family of the linear iteration solvers, for the iterative solutions of large sparse linear systems.     

Parallel iterative methods using factorized preconditioning matrices for solving elliptic equations on triangular grids

Parallel analogs of the variants of the incomplete Cholesky-conjugate gradient method and the modified incomplete Cholesky-conjugate gradient method for solving elliptic equations on uniform triangular and unstructured triangular grids on parallel computer systems with the MIMD architecture are considered. The construction of parallel methods is based on the use of various variants of ordering the grid points depending on the decomposition of the computation domain. Results of the theoretic and experimental studies of the convergence rate of these methods are presented. The solution of model problems on a moderate number processors is used to examine the efficiency of the proposed parallel methods.