An iterative algorithm for the least squares bisymmetric solutions of the matrix equations \(A_{1}XB_{1}=C_{1},A_{2}XB_{2}=C_{2}\)
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Publication:970024
DOI10.1016/j.mcm.2009.07.004zbMath1190.65061OpenAlexW2001090660MaRDI QIDQ970024
Publication date: 8 May 2010
Published in: Mathematical and Computer Modelling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.mcm.2009.07.004
iterative algorithmmatrix equationminimum Frobenius norm residual problemnormal equationoptimal approximation solutionleast squares bisymmetric solution
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Cites Work
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- The bisymmetric solutions of the matrix equation \(A_{1}X_{1}B_{1}+A_{2}X_{2}B_{2}+\cdots+A_{l}X_{l}B_{l}=C\) and its optimal approximation
- Computing a nearest symmetric positive semidefinite matrix
- A finite iterative method for solving a pair of linear matrix equations \((AXB,CXD)=(E,F)\)
- Practical Optimization
- The inverse problem of bisymmetric matrices with a submatrix constraint
- Iterative orthogonal direction methods for Hermitian minimum norm solutions of two consistent matrix equations
- A representation of the general common solution to the matrix equations \(A_1XB_1=C_1\) and \(A_2XB_2=C_2\) with applications
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