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An iterative algorithm for the least squares bisymmetric solutions of the matrix equations
Authors:Jing Cai  Guoliang Chen  
Affiliation:aDepartment of Mathematics, East China Normal University, Shanghai 200062, People’s Republic of China;bSchool of Science, Huzhou Teachers College, Huzhou Zhejiang 313000, People’s Republic of China
Abstract:In this paper, an iterative algorithm is constructed to solve the minimum Frobenius norm residual problem: minView the MathML source over bisymmetric matrices. By this algorithm, for any initial bisymmetric matrix X0, a solution X* can be obtained in finite iteration steps in the absence of roundoff errors, and the solution with least norm can be obtained by choosing a special kind of initial matrix. Furthermore, in the solution set of the above problem, the unique optimal approximation solution View the MathML source to a given matrix View the MathML source in the Frobenius norm can be derived by finding the least norm bisymmetric solution of a new corresponding minimum Frobenius norm problem. Given numerical examples show that the iterative algorithm is quite effective in actual computation.
Keywords:Iterative algorithm   Least squares bisymmetric solution   Matrix equation   Optimal approximation solution
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