期刊
COMPUTATIONAL & APPLIED MATHEMATICS
卷 37, 期 1, 页码 593-603出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s40314-016-0363-3
关键词
Generalized inverse eigenvalue problem; Hermitian-Hamiltonian matrix; Submatrix constraint; Optimal approximation
资金
- National Natural Science Foundations of China [61473332]
- Natural Science Foundation of Anhui Province [1508085MA12]
In this paper, a gradient-based iterative algorithm is proposed for finding the least-squares solutions of the following constrained generalized inverse eigenvalue problem: given X is an element of C-nxm, Lambda = diag(lambda(1), lambda(2),...,lambda(m)) is an element of C-mxm, find A*, B* is an element of C-nxn, such that parallel to AX -BX Lambda parallel to is minimized, where A*, B* are Hermitian-Hamiltonian except for a special submatrix. For any initial constrained matrices, a solution pair (A*, B*) can be obtained in finite iteration steps by this iterative algorithm in the absence of roundoff errors. The leastnorm solution can be obtained by choosing a special kind of initial matrix pencil. In addition, the unique optimal approximation solution to a given matrix pencil in the solution set of the above problem can also be obtained. A numerical example is given to show the efficiency of the proposed algorithm.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据