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Krylov Methods for Nonsymmetric Linear Systems - From Theory to Computations (Paperback, 1st ed. 2020)
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Krylov Methods for Nonsymmetric Linear Systems - From Theory to Computations (Paperback, 1st ed. 2020)
Series: Springer Series in Computational Mathematics, 57
Expected to ship within 10 - 15 working days
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This book aims to give an encyclopedic overview of the
state-of-the-art of Krylov subspace iterative methods for solving
nonsymmetric systems of algebraic linear equations and to study
their mathematical properties. Solving systems of algebraic linear
equations is among the most frequent problems in scientific
computing; it is used in many disciplines such as physics,
engineering, chemistry, biology, and several others. Krylov methods
have progressively emerged as the iterative methods with the
highest efficiency while being very robust for solving large linear
systems; they may be expected to remain so, independent of progress
in modern computer-related fields such as parallel and high
performance computing. The mathematical properties of the methods
are described and analyzed along with their behavior in finite
precision arithmetic. A number of numerical examples demonstrate
the properties and the behavior of the described methods. Also
considered are the methods' implementations and coding as Matlab
(R)-like functions. Methods which became popular recently are
considered in the general framework of Q-OR (quasi-orthogonal
)/Q-MR (quasi-minimum) residual methods. This book can be useful
for both practitioners and for readers who are more interested in
theory. Together with a review of the state-of-the-art, it presents
a number of recent theoretical results of the authors, some of them
unpublished, as well as a few original algorithms. Some of the
derived formulas might be useful for the design of possible new
methods or for future analysis. For the more applied user, the book
gives an up-to-date overview of the majority of the available
Krylov methods for nonsymmetric linear systems, including
well-known convergence properties and, as we said above, template
codes that can serve as the base for more individualized and
elaborate implementations.
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