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Mathematical Sciences

pp 1–9

First Online: 27 April 2017Received: 12 October 2016Accepted: 15 April 2017DOI: 10.1007-s40096-017-0223-3

Cite this article as: Refahi Sheikhani, A.H. & Kordrostami, S. Math Sci 2017. doi:10.1007-s40096-017-0223-3

Abstract

This paper presents two new iterative methods to compute generalized singular values and vectors of a large sparse matrix. To reach acceleration in the convergence process, we have used a different inner product instead of the common one, Euclidean one. Furthermore, at each restart, a different inner product has been chosen by the researchers. A number of numerical experiments illustrate the performance of the above-mentioned methods.

KeywordsGeneralized singular value Krylov subspace Iterative Sparse Mathematics Subject Classification15A18 65F10 65L15 



Author: A. H. Refahi Sheikhani - S. Kordrostami

Source: https://link.springer.com/



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