Volume 22, Issue 5
Computing a Nearest P-Symmetric Nonnegative Definite Matrix Under Linear Restriction

Hua Dai

DOI:

J. Comp. Math., 22 (2004), pp. 671-680

Published online: 2004-10

Preview Full PDF 171 1810
Export citation
  • Abstract

Let P be an $n\times n$ symmetric orthogonal matrix. A real $n\times n$ matrix A is called P-symmetric nonnegative definite if A is symmetric nonnegative definite and $(PA)^T=PA. This paper is concerned with a kind of inverse problem for P-symmetric nonnegative definite matrices: Given a real $n\times n$ matrix $\widetidle{A}$, real $n\times m$ matrices X and B, find an $n\times n$ P-symmetric nonnegative definite matrix A minimizing $||A-\widetidle{A}||_F$ subject to AX =B. Necessary and sufficient conditions are presented for the solvability of the problem. The expression of the solution to the problem is given. These results are applied to solve an inverse eigenvalue problem for P-symmetric nonnegative definite matrices.

  • Keywords

Inverse problem Matrix approximation Inverse eigenvalue problem Symmet-ric nonnegative definite matrix

  • AMS Subject Headings

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{JCM-22-671, author = {}, title = {Computing a Nearest P-Symmetric Nonnegative Definite Matrix Under Linear Restriction}, journal = {Journal of Computational Mathematics}, year = {2004}, volume = {22}, number = {5}, pages = {671--680}, abstract = { Let P be an $n\times n$ symmetric orthogonal matrix. A real $n\times n$ matrix A is called P-symmetric nonnegative definite if A is symmetric nonnegative definite and $(PA)^T=PA. This paper is concerned with a kind of inverse problem for P-symmetric nonnegative definite matrices: Given a real $n\times n$ matrix $\widetidle{A}$, real $n\times m$ matrices X and B, find an $n\times n$ P-symmetric nonnegative definite matrix A minimizing $||A-\widetidle{A}||_F$ subject to AX =B. Necessary and sufficient conditions are presented for the solvability of the problem. The expression of the solution to the problem is given. These results are applied to solve an inverse eigenvalue problem for P-symmetric nonnegative definite matrices. }, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/10295.html} }
TY - JOUR T1 - Computing a Nearest P-Symmetric Nonnegative Definite Matrix Under Linear Restriction JO - Journal of Computational Mathematics VL - 5 SP - 671 EP - 680 PY - 2004 DA - 2004/10 SN - 22 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/10295.html KW - Inverse problem KW - Matrix approximation KW - Inverse eigenvalue problem KW - Symmet-ric nonnegative definite matrix AB - Let P be an $n\times n$ symmetric orthogonal matrix. A real $n\times n$ matrix A is called P-symmetric nonnegative definite if A is symmetric nonnegative definite and $(PA)^T=PA. This paper is concerned with a kind of inverse problem for P-symmetric nonnegative definite matrices: Given a real $n\times n$ matrix $\widetidle{A}$, real $n\times m$ matrices X and B, find an $n\times n$ P-symmetric nonnegative definite matrix A minimizing $||A-\widetidle{A}||_F$ subject to AX =B. Necessary and sufficient conditions are presented for the solvability of the problem. The expression of the solution to the problem is given. These results are applied to solve an inverse eigenvalue problem for P-symmetric nonnegative definite matrices.
Hua Dai. (1970). Computing a Nearest P-Symmetric Nonnegative Definite Matrix Under Linear Restriction. Journal of Computational Mathematics. 22 (5). 671-680. doi:
Copy to clipboard
The citation has been copied to your clipboard