Semidefinite inverse eigenvalue problems with prescribed entries and partial eigendata

Semidefinite inverse eigenvalue problems with prescribed entries and partial eigendata
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具有规定条目和部分特征数据的半定反特征值问题

DOI:
10.1016/j.cam.2015.03.037
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发表时间:
2015-10
影响因子:
2.4
通讯作者:
Bai, Zheng-Jian
Bai, Zheng-Jian
中科院分区:
数学2区
文献类型:
--
作者:
Yao, Teng-Teng;Bai, Zheng-Jian

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研究了重构一个真实的n阶实矩阵C,使其在Frobenius范数下最接近于原预估计的真实的n阶实矩阵Co,并满足部分特征值的半定逆特征值问题,其中所需矩阵C应保持预估计矩阵Co的对称性、半正定性和预定元素.本文提出了求解半定特征值反问题的交替方向乘子法,并给出了三种相应的迭代算法。我们还将我们的方法扩展到下界的情况。数值实验表明,该方法求解半定特征值反问题是有效的。
In this paper, we study the semidefinite inverse eigenvalue problem of reconstructing a real n-by-n matrix C such that it is nearest to the original pre-estimated real n-by-n matrix C o in the Frobenius norm and satisfies the measured partial eigendata, where the required matrix C should preserve the symmetry, positive semidefiniteness, and the prescribed entries of the pre-estimated matrix C o. We propose the alternating direction method of multipliers for solving the semidefinite inverse eigenvalue problem, where three related iterative algorithms are presented. We also extend our method to the case of lower bounds. Numerical experiments are reported to illustrate the efficiency of the proposed method for solving semidefinite inverse eigenvalue problems.
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