四川师范大学学报（自然科学版）2012，Vol.35Issue(4)：473-477,5.DOI:10.3969/j.issn.1001-8395.2012.04.009
对称矩阵特征值反问题的最佳逼近解的一种数值解法
A Numerical Algorithm for the Optimal Approximation Solution to Inverse Eigenvalue Problem for Symmetric Matrices
摘要
Abstract
By applying the hybrid steepest descent method, this paper gives a general numerical algorithm to find the optimal approximation solution to inverse eigenvalue problem, AX = X(A), for symmetric matrices. For any given initial matrix, the optimal approximation can be derived by finite iteration steps. Some numerical examples are provided to illustrate the feasibility of the algorithm. Moreover, combined with projection algorithm, the numerical algorithm can also be used to calculate the optimal approximation solution to other convex constrained inverse eigenvalue problem, thus extending the applicable scope of this algorithm.关键词
复合最速下降法/特征值反问题/最佳逼近Key words
hybrid steepest descent method/ inverse eigenvalue problem/ optimal approximation分类
数理科学引用本文复制引用
何欢,孙合明,左环..对称矩阵特征值反问题的最佳逼近解的一种数值解法[J].四川师范大学学报（自然科学版）,2012,35(4):473-477,5.基金项目
国家自然科学基金(10871059)资助项目 （10871059）
