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Null space and eigenspace computations with additive preprocessing

Published: 25 July 2007 Publication History

Abstract

We propose and analyze additive preprocessing for computing a vector in the null space of a matrix and a basis for this space. Due to our preprocessing, instead of singular linear systems we solve nonsingular ones, which preserve the conditioning properties and the structure of the input matrices. We extend our preprocessing to decrease the size and the condition number of an ill conditioned input matrix. We also cover applications to the eigenspace computations and to generating effective preconditioners for a linear system of equations.

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cover image ACM Conferences
SNC '07: Proceedings of the 2007 international workshop on Symbolic-numeric computation
July 2007
218 pages
ISBN:9781595937445
DOI:10.1145/1277500
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 July 2007

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Author Tags

  1. additive preprocessing
  2. eigenspace computations
  3. ill conditioned matrices
  4. null space computations

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