The implicitly restarted multi-symplectic block-Lanczos method for large-scale Hermitian quaternion matrix eigenvalue problem and applications

被引:5
|
作者
Jia, Zhigang [1 ]
Liu, Xuan [1 ,2 ]
Zhao, Meixiang [1 ,3 ]
机构
[1] Jiangsu Normal Univ, Sch Math & Stat, Xuzhou 221116, Peoples R China
[2] Univ Macau, Dept Math, Macau, Peoples R China
[3] China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 221116, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-symplectic; Block-Lanczos method; Accelerate polynomials; Color image recognition; COMPUTATION; ALGORITHM;
D O I
10.1016/j.cam.2022.114664
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The large-scale Hermitian quaternion eigenvalue problem has become the key issue of color image recognition. However, there are still lack of efficient iterative methods of computing its partial eigenpairs. To solve this problem, a new implicitly restarted multisymplectic block-Lanczos method is proposed with generalizing the block and implicit restarting techniques to quaternion matrix eigenvalue computation. The proposed algorithm is applied to color image identification and approximation, and the experimental results demonstrate its efficiency and advantages to the existing algorithms. (c) 2022 Elsevier B.V. All rights reserved.
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页数:15
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