Computation of matrix functions with deflated restarting

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摘要

A deflated restarting Krylov subspace method for approximating a function of a matrix times a vector is proposed. In contrast to other Krylov subspace methods, the performance of the method in this paper is better. We further show that the deflating algorithm inherits the superlinear convergence property of its unrestarted counterpart for the entire function and present the results of numerical experiments.

论文关键词:Matrix functions,Krylov subspace approximation,Restarted Arnoldi method,Deflated restarting Krylov subspace method

论文评审过程:Received 28 December 2010, Revised 5 March 2012, Available online 24 July 2012.

论文官网地址:https://doi.org/10.1016/j.cam.2012.07.020