Preconditioning Conjugate Gradient Method by Málek Josef (12 results)

Condition: New. 114 pp., paperback, new. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Paperback. Condition: New. This first title in SIAM's Spotlights book series is about the interplay between modeling, analysis, discretization, matrix computation, and model reduction. The authors link PDE analysis, functional analysis, and calculus of variations with matrix iterative computation using Krylov subspace methods and address the challenges that arise during formulation of the mathematical model through to efficient numerical solution of the algebraic problem.The book's central concept, preconditioning of the conjugate gradient method, is traditionally developed algebraically using the preconditioned finite-dimensional algebraic system. In this text, however, preconditioning is connected to the PDE analysis, and the infinite-dimensional formulation of the conjugate gradient method and its discretization and preconditioning are linked together.This text challenges commonly held views, addresses widespread misunderstandings, and formulates thought-provoking open questions for further research.

Paperback. Condition: new. Paperback. The route from an applied problem to its numerical solution involves modeling, analysis, discretization, and the solution of the discretized problem. This book concerns the interplay of these stages and the challenges that arise. The authors link analysis of PDEs, functional analysis, and calculus of variations with iterative matrix computation using Krylov subspace methods. While preconditioning of the conjugate gradient method is traditionally developed algebraically using the preconditioned finite-dimensional algebraic system, the authors develop connections between preconditioning and PDEs. Additionally, links between the infinite-dimensional formulation of the conjugate gradient method, its discretization and preconditioning are explored. The book is intended for mathematicians, engineers, physicists, chemists, and any other researchers interested in the issues discussed. Aiming to improve understanding between researchers working on different solution stages, the book challenges commonly held views, addresses widespread misunderstandings, and formulates thought-provoking open questions for further research. Linking together Krylov subspace methods and preconditioning with analysis of PDEs and functional analysis, this book concerns the interplay between the stages leading from an applied problem to its numerical solution, and the challenges that arise. It is intended for mathematicians, engineers and scientists. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condition: Brand New. 114 pages. 9.80x6.70x0.30 inches. In Stock.

Condition: New. pp. 114.

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Condition: New. pp. 114.

Condition: New. A book linking matrix computation with analytic techniques to explore the links between different stages of solving an applied problem. Num Pages: 114 pages. BIC Classification: PBK. Category: (U) Tertiary Education (US: College). Dimension: 181 x 254 x 13. Weight in Grams: 220. . 2014. Paperback. . . . . Books ship from the US and Ireland.

Condition: New.

Paperback. Condition: new. Paperback. The route from an applied problem to its numerical solution involves modeling, analysis, discretization, and the solution of the discretized problem. This book concerns the interplay of these stages and the challenges that arise. The authors link analysis of PDEs, functional analysis, and calculus of variations with iterative matrix computation using Krylov subspace methods. While preconditioning of the conjugate gradient method is traditionally developed algebraically using the preconditioned finite-dimensional algebraic system, the authors develop connections between preconditioning and PDEs. Additionally, links between the infinite-dimensional formulation of the conjugate gradient method, its discretization and preconditioning are explored. The book is intended for mathematicians, engineers, physicists, chemists, and any other researchers interested in the issues discussed. Aiming to improve understanding between researchers working on different solution stages, the book challenges commonly held views, addresses widespread misunderstandings, and formulates thought-provoking open questions for further research. Linking together Krylov subspace methods and preconditioning with analysis of PDEs and functional analysis, this book concerns the interplay between the stages leading from an applied problem to its numerical solution, and the challenges that arise. It is intended for mathematicians, engineers and scientists. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Paperback. Condition: New. This first title in SIAM's Spotlights book series is about the interplay between modeling, analysis, discretization, matrix computation, and model reduction. The authors link PDE analysis, functional analysis, and calculus of variations with matrix iterative computation using Krylov subspace methods and address the challenges that arise during formulation of the mathematical model through to efficient numerical solution of the algebraic problem.The book's central concept, preconditioning of the conjugate gradient method, is traditionally developed algebraically using the preconditioned finite-dimensional algebraic system. In this text, however, preconditioning is connected to the PDE analysis, and the infinite-dimensional formulation of the conjugate gradient method and its discretization and preconditioning are linked together.This text challenges commonly held views, addresses widespread misunderstandings, and formulates thought-provoking open questions for further research.

Taschenbuch. Condition: Neu. Neuware - This first title in SIAM's Spotlights book series is about the interplay between modeling, analysis, discretization, matrix computation, and model reduction. The authors link PDE analysis, functional analysis, and calculus of variations with matrix iterative computation using Krylov subspace methods and address the challenges that arise during formulation of the mathematical model through to efficient numerical solution of the algebraic problem.The book's central concept, preconditioning of the conjugate gradient method, is traditionally developed algebraically using the preconditioned finite-dimensional algebraic system. In this text, however, preconditioning is connected to the PDE analysis, and the infinite-dimensional formulation of the conjugate gradient method and its discretization and preconditioning are linked together.This text challenges commonly held views, addresses widespread misunderstandings, and formulates thought-provoking open questions for further research.