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广义特征值极小扰动问题的一类黎曼共轭梯度法

孔令畅1, 魏科洋1, 周学林2,3, 李姣芬4   

  1. 1. 桂林电子科技大学数学与计算科学学院, 桂林 541004;
    2. 云南大学数学与统计学院, 昆明 650500;
    3. 桂林电子科技大学国际学院, 桂林 541004;
    4. 桂林电子科技大学数学与计算科学学院, 广西高校数据分析与计算重点实验室, 广西应用数学中心 (桂林电子科技大学), 广西自动检测技术与仪器重点实验室, 桂林 541004
  • 收稿日期:2021-03-25 出版日期:2022-11-14 发布日期:2022-11-08
  • 通讯作者: 周学林,Email:zhouxuelin0309@163.com.
  • 基金资助:
    国家自然科学基金资助项目(12261026,11961012,12201149),广西自然科学基金资助项目(2016GXNSFAA380074,2017GXNSFBA198082),广西科技基地和人才专项(2021AC06001),2022年桂林电子科技大学校级研究生创新项目(2022YCXS142),广西自动检测技术与仪器重点实验室基金(YQ21103,YQ22106)资助.

孔令畅, 魏科洋, 周学林, 李姣芬. 广义特征值极小扰动问题的一类黎曼共轭梯度法[J]. 计算数学, 2022, 44(4): 508-533.

Kong Lingchang, Wei Keyang, Zhou Xuelin, Li Jiaofen. A RIEMANNIAN CONJUGATE GRADIENT APPROACH FOR SOLVING THE GENERALIZED EIGENVALUE PROBLEM WITH MINIMAL PERTURBATION[J]. Mathematica Numerica Sinica, 2022, 44(4): 508-533.

A RIEMANNIAN CONJUGATE GRADIENT APPROACH FOR SOLVING THE GENERALIZED EIGENVALUE PROBLEM WITH MINIMAL PERTURBATION

Kong Lingchang1, Wei Keyang1, Zhou Xuelin2,3, Li Jiaofen4   

  1. 1. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China;
    2. School of Mathematics and Statistics, Yunan University, Kunming 650000, China;
    3. College of International Exchange, Guilin University of Electronic Technology, Guilin 541004, China;
    4. School of Mathematics and Computing Science, Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Center for Applied Mathematics of Guangxi (GUET), Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin, 541004, China
  • Received:2021-03-25 Online:2022-11-14 Published:2022-11-08
研究含参数$l$非方矩阵对广义特征值极小扰动问题所导出的一类复乘积流形约束矩阵最小二乘问题.与已有工作不同,本文直接针对复问题模型,结合复乘积流形的几何性质和欧式空间上的改进Fletcher-Reeves共轭梯度法,设计一类适用于问题模型的黎曼非线性共轭梯度求解算法,并给出全局收敛性分析.数值实验和数值比较表明该算法比参数$l=1$的已有算法收敛速度更快,与参数$l=n$的已有算法能得到相同精度的解.与部分其它流形优化相比与已有的黎曼Dai非线性共轭梯度法具有相当的迭代效率,与黎曼二阶算法相比单步迭代成本较低、总体迭代时间较少,与部分非流形优化算法相比在迭代效率上有明显优势.
This paper presents an efficient approach for solving a kind of complex product manifold constrained matrix least squares problem, which derived from the $l$ parameterized generalized eigenvalue problem for nonsquare matrix pencils with minimal perturbation. Different from the existing work, the paper directly focuses on the complex problem model, combining the geometric properties of the considered complex product manifold and basing on the modified Fletcher-Reeves nonlinear conjugate gradient method on Euclidean space, a class of Riemannian nonlinear conjugate gradient algorithm is designed for solving the underlying problem, and the global convergence analysis is given. Numerical experiments and numerical comparisons are given to show that the proposed algorithm converges faster than the existing algorithm with parameter $l=1$, and can get the same accuracy as the existing algorithm with parameter $l=n$. Detailed comparisons with some latest methods, including some other gradient-based methods, some Riemannian second-order algorithms, and two non-manifold optimization algorithms are also provided to show the merits of the proposed approach.

MR(2010)主题分类: 

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