Any book on the solution of nonsingular systems of equations is bound to start with Ax= J, but here, A is assumed to be symmetric. These systems arise frequently in scientific computing, for example, from the discretization by finite differences or by finite elements of partial differential equations. Usually, the resulting coefficient matrix A is large, but sparse. In many cases, the need to store the matrix factors rules out the application of direct solvers, such as Gaussian elimination in which case the only alternative is to use iterative methods. A natural way to exploit the sparsity structure of A is to design iterative schemes that involve the coefficient matrix only in the form of matrix-vector products. To achieve this goal, most iterative methods generate iterates Xn by the simple rule Xn = Xo + Qn-l(A)ro, where ro = f-Axo denotes the initial residual and Qn-l is some polynomial of degree n - 1. The idea behind such polynomial based iteration methods is to choose Qn-l such that the scheme converges as fast as possible.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
EUR 2,27 expédition vers Etats-Unis
Destinations, frais et délaisEUR 2,27 expédition vers Etats-Unis
Destinations, frais et délaisVendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 20348009-n
Quantité disponible : 15 disponible(s)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Mar3113020322117
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Mason, OH, Etats-Unis
Paperback. Etat : new. Paperback. Any book on the solution of nonsingular systems of equations is bound to start with Ax= J, but here, A is assumed to be symmetric. These systems arise frequently in scientific computing, for example, from the discretization by finite differences or by finite elements of partial differential equations. Usually, the resulting coefficient matrix A is large, but sparse. In many cases, the need to store the matrix factors rules out the application of direct solvers, such as Gaussian elimination in which case the only alternative is to use iterative methods. A natural way to exploit the sparsity structure of A is to design iterative schemes that involve the coefficient matrix only in the form of matrix-vector products. To achieve this goal, most iterative methods generate iterates Xn by the simple rule Xn = Xo + Qn-l(A)ro, where ro = f-Axo denotes the initial residual and Qn-l is some polynomial of degree n - 1. The idea behind such polynomial based iteration methods is to choose Qn-l such that the scheme converges as fast as possible. Any book on the solution of nonsingular systems of equations is bound to start with Ax= J, but here, A is assumed to be symmetric. These systems arise frequently in scientific computing, for example, from the discretization by finite differences or by finite elements of partial differential equations. Usually, the resulting coefficient matrix A is large, but sparse. In many cases, the need to store the matrix factors rules out the application of direct solvers, such as Gaussian elimination in which case the only alternative is to use iterative methods. A natural way to exploit the sparsity structure of A is to design iterative schemes that involve the coefficient matrix only in the form of matrix-vector products. To achieve this goal, most iterative methods generate iterates Xn by the simple rule Xn = Xo + Qn-l(A)ro, where ro = f-Axo denotes the initial residual and Qn-l is some polynomial of degree n - 1. The idea behind such polynomial based iteration methods is to choose Qn-l such that the scheme converges as fast as possible. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783663111092
Quantité disponible : 1 disponible(s)
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 20348009
Quantité disponible : 15 disponible(s)
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9783663111092
Quantité disponible : Plus de 20 disponibles
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9783663111092_new
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9783663111092
Quantité disponible : 10 disponible(s)
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Contents: Introduction - Orthogonal Polynomials - Chebyshev and Optimal Polynomials - Orthogonal Polynomials and Krylow Subspaces - Estimating the Spectrum and the Distribution function - Parameter Free Methods - Parameter Dependent Methods - The Stokes Problem - Approximating the A-Norm - Bibliography - Notation - Index 284 pp. Deutsch. N° de réf. du vendeur 9783663111092
Quantité disponible : 2 disponible(s)
Vendeur : Books Puddle, New York, NY, Etats-Unis
Etat : New. pp. 284 Index. N° de réf. du vendeur 26142298285
Quantité disponible : 4 disponible(s)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. Print on Demand pp. 284 67:B&W 6.69 x 9.61 in or 244 x 170 mm (Pinched Crown) Perfect Bound on White w/Gloss Lam. N° de réf. du vendeur 135066482
Quantité disponible : 4 disponible(s)