LSQR iterative common symmetric solutions to matrix equations \(AXB = E\) and \(CXD = F\)
From MaRDI portal
Publication:708164
DOI10.1016/j.amc.2010.05.053zbMath1206.65142OpenAlexW2070201384MaRDI QIDQ708164
Tiejun Zhou, Zhen-yun Peng, Ya-bo Chen
Publication date: 11 October 2010
Published in: Applied Mathematics and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.amc.2010.05.053
Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).
Related Items (7)
A unified treatment for the restricted solutions of the matrix equation \(AXB=C\) ⋮ Symmetric least squares solution of a class of Sylvester matrix equations via MINIRES algorithm ⋮ A new iterative algorithm for solving a class of matrix nearness problem ⋮ Alternating direction methods for solving a class of Sylvester-like matrix equations ⋮ An efficient method for special least squares solution of the complex matrix equation \((AXB,CXD)=(E,F)\) ⋮ Matrix LSQR algorithm for structured solutions to quaternionic least squares problem ⋮ Conjugate gradient-like algorithms for constrained operator equation related to quadratic inverse eigenvalue problems
Uses Software
Cites Work
- The matrix nearness problem for symmetric matrices associated with the matrix equation \([A^{T}XA, B^{T}XB = [C, D]\)]
- An efficient algorithm for the least-squares reflexive solution of the matrix equation \(A_{1}XB_{1} = C_{1}, A_{2}XB_{2} = C_{2}\)
- An iterative method for symmetric solutions and optimal approximation solution of the system of matrix equations \(A_{1}XB_{1} = C_{1}, A_{2}XB_{2} = C_{2}\)
- A new version of successive approximations method for solving Sylvester matrix equations
- A numerical algorithm for Lyapunov equations
- An iterative algorithm for the reflexive solutions of the generalized coupled Sylvester matrix equations and its optimal approximation
- Gradient based iterative solutions for general linear matrix equations
- A shift-splitting hierarchical identification method for solving Lyapunov matrix equations
- On the existence of a common solution \(X\) to the matrix equations \(A_{i} XB_{j}\)=\(C_{ij}\), \((i,j){\in}\Gamma\).
- Hierarchical gradient-based identification of multivariable discrete-time systems
- An iteration method for the symmetric solutions and the optimal approximation solution of the matrix equation \(AXB\)=\(C\)
- A minimal residual algorithm for the inconsistent matrix equation \(AXB = C\) over symmetric matrices
- A finite iterative method for solving a pair of linear matrix equations \((AXB,CXD)=(E,F)\)
- Iterative solutions of the generalized Sylvester matrix equations by using the hierarchical identification principle
- Iterative least-squares solutions of coupled sylvester matrix equations
- Global least squares method (Gl-LSQR) for solving general linear systems with several right-hand sides
- An iterative method for the least squares symmetric solution of the linear matrix equation \(AXB = C\)
- On Iterative Solutions of General Coupled Matrix Equations
- An efficient iterative method for solving the matrix equationAXB +CYD =E
- LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
- Hierarchical least squares identification methods for multivariable systems
- Gradient based iterative algorithms for solving a class of matrix equations
- Calculating the Singular Values and Pseudo-Inverse of a Matrix
This page was built for publication: LSQR iterative common symmetric solutions to matrix equations \(AXB = E\) and \(CXD = F\)
