Norm-constrained least-squares solutions to the matrix equation \(A X B = C\)

DOI10.1155/2013/781276zbMath1470.65091OpenAlexW1982051778WikidataQ58917436 ScholiaQ58917436MaRDI QIDQ2319099

An-Bao Xu, Zhen-yun Peng

Publication date: 16 August 2019

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/781276

Mathematics Subject Classification ID

Matrix equations and identities (15A24) Numerical linear algebra (65F99)

Related Items (2)

Iterative optimal solutions of linear matrix equations for hyperspectral and multispectral image fusing ⋮ Iterative algorithms for least-squares solutions of a quaternion matrix equation

Uses Software

• GQTPAR
• HSL-VF05

Cites Work

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• New matrix iterative methods for constraint solutions of the matrix equation \(AXB=C\)
• An iteration method for the symmetric solutions and the optimal approximation solution of the matrix equation \(AXB\)=\(C\)
• An iterative method for the skew-symmetric solution and the optimal approximate solution of the matrix equation \(AXB=C\)
• An efficient algorithm for the generalized centro-symmetric solution of matrix equation \(AXB = C\)
• A Trust-Region Approach to the Regularization of Large-Scale Discrete Forms of Ill-Posed Problems
• Computing a Trust Region Step
• The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
• Solving the Trust-Region Subproblem using the Lanczos Method
• A matrix LSQR iterative method to solve matrix equationAXB=C

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