Book Review: Krylov subspace methods: principles and analysis

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Convergence analysis of Krylov subspace methods †

One of the most powerful tools for solving large and sparse systems of linear algebraic equations is a class of iterative methods called Krylov subspace methods. Their significant advantages like low memory requirements and good approximation properties make them very popular, and they are widely used in applications throughout science and engineering. The use of the Krylov subspaces in iterati...

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Analysis of Augmented Krylov Subspace Methods

Residual norm estimates are derived for a general class of methods based on projection techniques on subspaces of the form K m + W, where K m is the standard Krylov subspace associated with the original linear system, and W is some other subspace. Thesèaugmented Krylov subspace methods' include eigenvalue deeation techniques as well as block-Krylov methods. Residual bounds are established which...

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Krylov subspace methods and minimal residuals

We give a concise introduction to some recent developments of Krylov subspace methods (in particular, the method of minimal residuals) and tendencies in the design and analysis of good preconditioners.

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ژورنال

عنوان ژورنال: Bulletin of the American Mathematical Society

سال: 2014

ISSN: 0273-0979,1088-9485

DOI: 10.1090/s0273-0979-2014-01473-9