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• W2962893506 abstract "In this paper we propose a new iterative method to hierarchically compute a relatively large number of leftmost eigenpairs of a sparse symmetric positive matrix under the multiresolution operator compression framework. We exploit the well-conditioned property of every decomposition component by integrating the multiresolution framework into the implicitly restarted Lanczos method. We achieve this combination by proposing an extension-refinement iterative scheme, in which the intrinsic idea is to decompose the target spectrum into several segments such that the corresponding eigenproblem in each segment is well-conditioned. Theoretical analysis and numerical illustration are also reported to illustrate the efficiency and effectiveness of this algorithm." @default.
• W2962893506 created "2019-07-30" @default.
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• W2962893506 date "2019-01-01" @default.
• W2962893506 modified "2023-10-15" @default.
• W2962893506 title "A Fast Hierarchically Preconditioned Eigensolver Based on Multiresolution Matrix Decomposition" @default.
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• W2962893506 doi "https://doi.org/10.1137/18m1180827" @default.
• W2962893506 hasPublicationYear "2019" @default.
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