Abstract

A variation of Paige’s algorithm is presented for computing the generalized singular value decomposition (GSVD) of two matrices A and B. There are two innovations. The first is a new preprocessing step which reduces A and B to upper triangular forms satisfying certain rank conditions. The second is a new $2 \times 2$ triangular GSVD algorithm, which constitutes the inner loop of Paige’s algorithm. Proofs of stability and high accuracy of the $2 \times 2$ GSVD algorithm are presented and are demonstrated using examples on which all previous algorithms fail.

MSC codes

  1. 65F30
  2. G1.3

Keywords

  1. generalized singular value decomposition
  2. CS decomposition
  3. matrix decomposition
  4. Jacobi algorithm
  5. Kogbetliantz algorithm

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Published In

cover image SIAM Journal on Scientific Computing
SIAM Journal on Scientific Computing
Pages: 1464 - 1486
ISSN (online): 1095-7197

History

Submitted: 19 August 1991
Accepted: 17 December 1992
Published online: 13 July 2006

MSC codes

  1. 65F30
  2. G1.3

Keywords

  1. generalized singular value decomposition
  2. CS decomposition
  3. matrix decomposition
  4. Jacobi algorithm
  5. Kogbetliantz algorithm

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