Error Control and Adaptivity in Scientific Computing [electronic resource] /

One of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. Modern simulation tools are not used only by experts, however, and reliability has therefore become an important issue, meaning that it is not sufficient for a simulation package merely to print out some numbers, claiming them to be the desired results. An estimate of the associated error is also needed. The errors may derive from many sources: errors in the model, errors in discretization, rounding errors, etc. Unfortunately, this situation does not obtain for current packages and there is a great deal of room for improvement. Only if the error can be estimated is it possible to do something to reduce it. The contributions in this book cover many aspects of the subject, the main topics being error estimates and error control in numerical linear algebra algorithms (closely related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.

Saved in:
Bibliographic Details
Main Authors: Bulgak, Haydar. editor., Zenger, Christoph. editor., SpringerLink (Online service)
Format: Texto biblioteca
Language:eng
Published: Dordrecht : Springer Netherlands : Imprint: Springer, 1999
Subjects:Mathematics., Numerical analysis., Computer mathematics., Algorithms., Probabilities., Applied mathematics., Engineering mathematics., Numerical Analysis., Probability Theory and Stochastic Processes., Computational Mathematics and Numerical Analysis., Numeric Computing., Appl.Mathematics/Computational Methods of Engineering.,
Online Access:http://dx.doi.org/10.1007/978-94-011-4647-0
Tags: Add Tag
No Tags, Be the first to tag this record!
id KOHA-OAI-TEST:197688
record_format koha
spelling KOHA-OAI-TEST:1976882018-07-30T23:23:57ZError Control and Adaptivity in Scientific Computing [electronic resource] / Bulgak, Haydar. editor. Zenger, Christoph. editor. SpringerLink (Online service) textDordrecht : Springer Netherlands : Imprint: Springer,1999.engOne of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. Modern simulation tools are not used only by experts, however, and reliability has therefore become an important issue, meaning that it is not sufficient for a simulation package merely to print out some numbers, claiming them to be the desired results. An estimate of the associated error is also needed. The errors may derive from many sources: errors in the model, errors in discretization, rounding errors, etc. Unfortunately, this situation does not obtain for current packages and there is a great deal of room for improvement. Only if the error can be estimated is it possible to do something to reduce it. The contributions in this book cover many aspects of the subject, the main topics being error estimates and error control in numerical linear algebra algorithms (closely related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.Interval Arithmetic Tools for Range Approximation and Inclusion of Zeros -- A New Concept of Construction of Adaptive Calculation Models for Hyperbolic Problems -- Error Estimates in Linear Systems -- Error Estimates in Padé Approximation -- Error Estimates and Convergence Acceleration -- Pseudoeigenvalues Spectral Portrait of a Matrix and their Connections with Different Criteria of Stability -- Error Control for Adaptive Sparse Grids -- Orthogonal Matrix Decompositions in Systems and Control -- Model Reduction of Large-Scale Systems, Rational Krylov versus Balancing Techniques -- Adaptive Symplectic and Reversible Integrators -- Domain Decomposition Methods for Compressible Flows -- Error Control in Finite Element Computations. An introduction to error estimation and mesh-size adaption -- Verified Solution of Large Linear and Nonlinear Systems -- The Accuracy of Numerical Models for Continuum Problems -- Domain Decomposition Methods for Elliptic Partial Differential Equations.One of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. Modern simulation tools are not used only by experts, however, and reliability has therefore become an important issue, meaning that it is not sufficient for a simulation package merely to print out some numbers, claiming them to be the desired results. An estimate of the associated error is also needed. The errors may derive from many sources: errors in the model, errors in discretization, rounding errors, etc. Unfortunately, this situation does not obtain for current packages and there is a great deal of room for improvement. Only if the error can be estimated is it possible to do something to reduce it. The contributions in this book cover many aspects of the subject, the main topics being error estimates and error control in numerical linear algebra algorithms (closely related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.Mathematics.Numerical analysis.Computer mathematics.Algorithms.Probabilities.Applied mathematics.Engineering mathematics.Mathematics.Numerical Analysis.Probability Theory and Stochastic Processes.Computational Mathematics and Numerical Analysis.Numeric Computing.Algorithms.Appl.Mathematics/Computational Methods of Engineering.Springer eBookshttp://dx.doi.org/10.1007/978-94-011-4647-0URN:ISBN:9789401146470
institution COLPOS
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
En linea
databasecode cat-colpos
tag biblioteca
region America del Norte
libraryname Departamento de documentación y biblioteca de COLPOS
language eng
topic Mathematics.
Numerical analysis.
Computer mathematics.
Algorithms.
Probabilities.
Applied mathematics.
Engineering mathematics.
Mathematics.
Numerical Analysis.
Probability Theory and Stochastic Processes.
Computational Mathematics and Numerical Analysis.
Numeric Computing.
Algorithms.
Appl.Mathematics/Computational Methods of Engineering.
Mathematics.
Numerical analysis.
Computer mathematics.
Algorithms.
Probabilities.
Applied mathematics.
Engineering mathematics.
Mathematics.
Numerical Analysis.
Probability Theory and Stochastic Processes.
Computational Mathematics and Numerical Analysis.
Numeric Computing.
Algorithms.
Appl.Mathematics/Computational Methods of Engineering.
spellingShingle Mathematics.
Numerical analysis.
Computer mathematics.
Algorithms.
Probabilities.
Applied mathematics.
Engineering mathematics.
Mathematics.
Numerical Analysis.
Probability Theory and Stochastic Processes.
Computational Mathematics and Numerical Analysis.
Numeric Computing.
Algorithms.
Appl.Mathematics/Computational Methods of Engineering.
Mathematics.
Numerical analysis.
Computer mathematics.
Algorithms.
Probabilities.
Applied mathematics.
Engineering mathematics.
Mathematics.
Numerical Analysis.
Probability Theory and Stochastic Processes.
Computational Mathematics and Numerical Analysis.
Numeric Computing.
Algorithms.
Appl.Mathematics/Computational Methods of Engineering.
Bulgak, Haydar. editor.
Zenger, Christoph. editor.
SpringerLink (Online service)
Error Control and Adaptivity in Scientific Computing [electronic resource] /
description One of the main ways by which we can understand complex processes is to create computerised numerical simulation models of them. Modern simulation tools are not used only by experts, however, and reliability has therefore become an important issue, meaning that it is not sufficient for a simulation package merely to print out some numbers, claiming them to be the desired results. An estimate of the associated error is also needed. The errors may derive from many sources: errors in the model, errors in discretization, rounding errors, etc. Unfortunately, this situation does not obtain for current packages and there is a great deal of room for improvement. Only if the error can be estimated is it possible to do something to reduce it. The contributions in this book cover many aspects of the subject, the main topics being error estimates and error control in numerical linear algebra algorithms (closely related to the concept of condition numbers), interval arithmetic and adaptivity for continuous models.
format Texto
topic_facet Mathematics.
Numerical analysis.
Computer mathematics.
Algorithms.
Probabilities.
Applied mathematics.
Engineering mathematics.
Mathematics.
Numerical Analysis.
Probability Theory and Stochastic Processes.
Computational Mathematics and Numerical Analysis.
Numeric Computing.
Algorithms.
Appl.Mathematics/Computational Methods of Engineering.
author Bulgak, Haydar. editor.
Zenger, Christoph. editor.
SpringerLink (Online service)
author_facet Bulgak, Haydar. editor.
Zenger, Christoph. editor.
SpringerLink (Online service)
author_sort Bulgak, Haydar. editor.
title Error Control and Adaptivity in Scientific Computing [electronic resource] /
title_short Error Control and Adaptivity in Scientific Computing [electronic resource] /
title_full Error Control and Adaptivity in Scientific Computing [electronic resource] /
title_fullStr Error Control and Adaptivity in Scientific Computing [electronic resource] /
title_full_unstemmed Error Control and Adaptivity in Scientific Computing [electronic resource] /
title_sort error control and adaptivity in scientific computing [electronic resource] /
publisher Dordrecht : Springer Netherlands : Imprint: Springer,
publishDate 1999
url http://dx.doi.org/10.1007/978-94-011-4647-0
work_keys_str_mv AT bulgakhaydareditor errorcontrolandadaptivityinscientificcomputingelectronicresource
AT zengerchristopheditor errorcontrolandadaptivityinscientificcomputingelectronicresource
AT springerlinkonlineservice errorcontrolandadaptivityinscientificcomputingelectronicresource
_version_ 1756267051076288512