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The Anti-symmetric Orthogonal Anti-symmetric Least Squre Solutions of Matrix Equation A~TXA=B

Xi-Yan Hu

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Abstract

Applying the generalized singular value decomposition (GSVD) of matrices, we obtain the expression of the anti-symmetric orthogonal anti-symmetric with a symmetric orthogonal matrix P least square solutions of the matrix equation ATXA=B(A∈Rn×m, B∈Rm×m), and derive the corresponding solution set of the equation, the explicit expressions of the optimal approximation solution to the given matrix and minimum norm solution.

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Applying the generalized singular value decomposition (GSVD) of matrices, we obtain the expression of the anti-symmetric orthogonal anti-symmetric with a symmetric orthogonal matrix P least square solutions of the matrix equation ATXA=B(A∈Rn×m, B∈Rm×m), and derive the corresponding solution set of the equation, the explicit expressions of the optimal approximation solution to the given matrix and minimum norm solution.

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Available abstract

Applying the generalized singular value decomposition (GSVD) of matrices, we obtain the expression of the anti-symmetric orthogonal anti-symmetric with a symmetric orthogonal matrix P least square solutions of the matrix equation ATXA=B(A∈Rn×m, B∈Rm×m), and derive the corresponding solution set of the equation, the explicit expressions of the optimal approximation solution to the given matrix and minimum norm solution.

Key concepts: Mathematics, Symmetric matrix, Orthogonal matrix, Matrix (chemical analysis), Singular value decomposition, Square matrix, Mathematical analysis, Combinatorics

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