It is not uncommon to encounter problems that lead to large, sparse linear systems with coefficient matrices that are invertible and sparse, but have little other structure. In such problems the solution u=A¹ƒ is typically calculated only to acurately compute functionals of the solution, L(u). This paper determines a method that converges rapidly to the functional's value. Specifially, a modified bi-conjugate gradient algorithm is found to generate convergence to the solution of linear functionals, L(u), much more rapidly than convergence to the linear system solution u
AbstractConjugate gradient type methods are discussed for unsymmetric and inconsistent system of equ...
A Modified Conjugate Gradient scheme to solve sparse linear systems with positive definite coefficie...
The well-known Conjugate Gradient (CG) method minimizes a strictly convex quadratic function for s...
It is not uncommon to encounter problems that lead to large, sparse linear systems with coefficient ...
Problems in many applications lead to large, sparse linear systems with coefficient matrices that ar...
AbstractThis paper presents a conjugate gradient method for solving systems of linear inequalities. ...
Abstract. This short note is on the derivation and convergence of a popular algorithm for minimizati...
AbstractLet A ε ℛm × n(with m ⩾ n and rank (A) = n) and b ε ℛm × 1 be given. Assume that an approxim...
AbstractThe development of the Lanczos algorithm for finding eigenvalues of large sparse symmetric m...
. The Conjugate Gradient Squared (CGS) is a well-known and widely used iterative method for solving ...
AbstractWe consider large sparse linear systems Ax = b with complex symmetric coefficient matrices A...
A modified conjugate gradient algorithm is proposed which uses a gradient average window to pro-vide...
. In this paper we analyze the BiCG algorithm in finite precision arithmetic and suggest reasons for...
The paper introduces the main idea of the conjugate gradient method for solving large systems of lin...
AbstractThe Conjugate Gradient (CG) method and the Conjugate Residual (CR) method are Krylov subspac...
AbstractConjugate gradient type methods are discussed for unsymmetric and inconsistent system of equ...
A Modified Conjugate Gradient scheme to solve sparse linear systems with positive definite coefficie...
The well-known Conjugate Gradient (CG) method minimizes a strictly convex quadratic function for s...
It is not uncommon to encounter problems that lead to large, sparse linear systems with coefficient ...
Problems in many applications lead to large, sparse linear systems with coefficient matrices that ar...
AbstractThis paper presents a conjugate gradient method for solving systems of linear inequalities. ...
Abstract. This short note is on the derivation and convergence of a popular algorithm for minimizati...
AbstractLet A ε ℛm × n(with m ⩾ n and rank (A) = n) and b ε ℛm × 1 be given. Assume that an approxim...
AbstractThe development of the Lanczos algorithm for finding eigenvalues of large sparse symmetric m...
. The Conjugate Gradient Squared (CGS) is a well-known and widely used iterative method for solving ...
AbstractWe consider large sparse linear systems Ax = b with complex symmetric coefficient matrices A...
A modified conjugate gradient algorithm is proposed which uses a gradient average window to pro-vide...
. In this paper we analyze the BiCG algorithm in finite precision arithmetic and suggest reasons for...
The paper introduces the main idea of the conjugate gradient method for solving large systems of lin...
AbstractThe Conjugate Gradient (CG) method and the Conjugate Residual (CR) method are Krylov subspac...
AbstractConjugate gradient type methods are discussed for unsymmetric and inconsistent system of equ...
A Modified Conjugate Gradient scheme to solve sparse linear systems with positive definite coefficie...
The well-known Conjugate Gradient (CG) method minimizes a strictly convex quadratic function for s...