activity
20172026
most citedA skew-symmetric Lanczos bidiagonalization method for computing several largest eigenpairs of a large skew-symmetric matrix

5 citations · 16 across the 8 of their papers we have counts for

collaborators

8 papers

math.NA2026

JD-V: A new variant of Jacobi--Davidson method for large Hermitian eigenproblems

Jinzhi Huang

A novel variant of the Jacobi-Davidson (JD) type method for Hermitian eigenvalue problems, designated as JD-V, is proposed based on a newly designed correction equation, whose solu…

math.NA2026

An LSQR-based algorithm for large-scale null space computations

Jinzhi Huang

Computing the null space and null vectors of large-scale matrices is a fundamental task in numerical linear algebra and scientific computing. In this paper, an LSQR-based algorithm…

math.NA2024

New Jacobi--Davidson type methods for the large SVD computations

Jinzhi Huang, Zhongxiao Jia

In a Jacobi--Davidson (JD) type method for singular value decomposition (SVD) problems, called JDSVD, a large symmetric and generally indefinite correction equation is solved itera…

math.NA2023★ 1 cited

Refined and refined harmonic Jacobi--Davidson methods for computing several GSVD components of a large regular matrix pair

Jinzhi Huang, Zhongxiao Jia

Three refined and refined harmonic extraction-based Jacobi--Davidson (JD) type methods are proposed, and their thick-restart algorithms with deflation and purgation are developed t…

math.NA2022★ 5 cited

A skew-symmetric Lanczos bidiagonalization method for computing several largest eigenpairs of a large skew-symmetric matrix

Jinzhi Huang, Zhongxiao Jia

The spectral decomposition of a real skew-symmetric matrix can be mathematically transformed into a specific structured singular value decomposition (SVD) of . Based on such…

math.NA2022★ 5 cited

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

Jinzhi Huang, Zhongxiao Jia

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…

math.NA2020★ 5 cited

A cross-product free Jacobi-Davidson type method for computing a partial generalized singular value decomposition (GSVD) of a large matrix pair

Jinzhi Huang, Zhongxiao Jia

A Cross-Product Free (CPF) Jacobi-Davidson (JD) type method is proposed to compute a partial generalized singular value decomposition (GSVD) of a large regular matrix pair .…

math.NA2017

On inner iterations of Jacobi-Davidson type methods for large SVD computations

Jinzhi Huang, Zhongxiao Jia

We make a convergence analysis of the harmonic and refined harmonic extraction versions of Jacobi-Davidson SVD (JDSVD) type methods for computing one or more interior singular trip…