• Corpus ID: 245837530

Two harmonic Jacobi-Davidson methods for computing a partial generalized singular value decomposition of a large matrix pair

@article{Huang2022TwoHJ,
  title={Two harmonic Jacobi-Davidson methods for computing a partial generalized singular value decomposition of a large matrix pair},
  author={Jinzhi Huang and Zhongxiao Jia},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.02903}
}
Two harmonic extraction based Jacobi–Davidson (JD) type algorithms are proposed to compute a partial generalized singular value decomposition (GSVD) of a large regular matrix pair. They are called cross product-free (CPF) and inverse-free (IF) harmonic JDGSVD algorithms, abbreviated as CPF-HJDGSVD and IF-HJDGSVD, respectively. Compared with the standard extraction based JDGSVD algorithm, the harmonic extraction based algorithms converge more regularly and suit better for computing GSVD… 

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