Abstract
In this paper a preconditioned iterative method suitable for the solution of the generalized eigenvalue problem is presented. The proposed method is suitable for the determination of the extreme eigenvalues and their corresponding eigenvectors of the large sparse matrices derived from finite element/difference discretisation of partial differential equations. The new strategy when coupled with the conjugate gradient algorithm yields a powerful method for this class of problems.
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References
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© 1983 Springer-Verlag
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Evans, D.J. (1983). Preconditioned iterative methods for the generalized eigenvalue problem. In: Kågström, B., Ruhe, A. (eds) Matrix Pencils. Lecture Notes in Mathematics, vol 973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0062102
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DOI: https://doi.org/10.1007/BFb0062102
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-11983-8
Online ISBN: 978-3-540-39447-1
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