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Computer Solution of Large Linear Systems
Computer Solution of Large Linear Systems
Knygos.lt klubas Knygos.lt nariams
260,74 €
-30%
Įprastai
372,49 €
  • Išsiųsime per 12–18 d.d.
This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A…
  • Leidėjas:
  • ISBN-10: 044450169X
  • ISBN-13: 9780444501691
  • Formatas: 15.6 x 23.4 x 4.1 cm, kieti viršeliai
  • Kalba: Anglų

Computer Solution of Large Linear Systems (el. knyga) (skaityta knyga) | knygos.lt

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This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A particular emphasis is put on the conjugate gradient as well as conjugate gradient -like methods for non symmetric problems. Most efficient preconditioners used to speed up convergence are studied. A chapter is devoted to the multigrid method and the book ends with domain decomposition algorithms that are well suited for solving linear systems on parallel computers.

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  • Autorius: Gerard Meurant
  • Leidėjas:
  • ISBN-10: 044450169X
  • ISBN-13: 9780444501691
  • Formatas: 15.6 x 23.4 x 4.1 cm, kieti viršeliai
  • Kalba: Anglų

This book deals with numerical methods for solving large sparse linear systems of equations, particularly those arising from the discretization of partial differential equations. It covers both direct and iterative methods. Direct methods which are considered are variants of Gaussian elimination and fast solvers for separable partial differential equations in rectangular domains. The book reviews the classical iterative methods like Jacobi, Gauss-Seidel and alternating directions algorithms. A particular emphasis is put on the conjugate gradient as well as conjugate gradient -like methods for non symmetric problems. Most efficient preconditioners used to speed up convergence are studied. A chapter is devoted to the multigrid method and the book ends with domain decomposition algorithms that are well suited for solving linear systems on parallel computers.

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