Dai Hua

Doctoral Degree in Science

With Certificate of Graduation for Doctorate Study

南京大学

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Gender:Male
Business Address:江宁校区理学院大楼368室
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Implicitly Restarted Refined Generalised Arnoldi Method with Deflation for the Polynomial Eigenvalue Problem

Date of Publication:2018-02-01 Hits:

Affiliation of Author(s):理学院
Journal:EAST ASIAN JOURNAL ON APPLIED MATHEMATICS
Key Words:Polynomial eigenvalue problem generalised Arnoldi method refinement implicit restarting non-equivalence low-rank deflation
Abstract:Based on the generalised Arnoldi procedure, we develop an implicitly restarted generalised Arnoldi method for solving the large-scale polynomial eigenvalue problem. By combining implicit restarting with the refinement scheme, we present an implicitly restarted refined generalised Arnoldi (IRGAR) method. To avoid repeated converged eigenpairs in the later iteration, we develop a novel non-equivalence low-rank deflation technique and propose a deflated and implicitly restarted refined generalised Arnoldi method (DIRGAR). Some numerical experiments show that this DIRGAR method is efficient and robust.
ISSN No.:2079-7362
Translation or Not:no
Date of Publication:2018-02-01
Co-author:ww
Correspondence Author:Dai Hua