2010•Journal of Hefei University of TechnologyRequires access

Symmetric and skew-antisymmetric least square solutions of matrix equation A~TXA=C

Kang Su-ling

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Abstract

By applying the generalized singular value decomposition(GSVD) of matrix pairs and the properties of symmetric and skew-antisymmetric matrix,the expression of the symmetric and skew-antisymmetric least square solutions of the matrix equation ATXA=C is given in this paper. In addition,according to the property of orthogonal matrix,the explicit expression of minimum norm solution is also derived in the corresponding symmetric and skew-antisymmetric solution set of the matrix equation.

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What this paper is about

By applying the generalized singular value decomposition(GSVD) of matrix pairs and the properties of symmetric and skew-antisymmetric matrix,the expression of the symmetric and skew-antisymmetric least square solutions of the matrix equation ATXA=C is given in this paper. In addition,according to the property of orthogonal matrix,the explicit expression of minimum norm solution is also derived in the corresponding symmetric and skew-antisymmetric solution set of the matrix equation.

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Available abstract

By applying the generalized singular value decomposition(GSVD) of matrix pairs and the properties of symmetric and skew-antisymmetric matrix,the expression of the symmetric and skew-antisymmetric least square solutions of the matrix equation ATXA=C is given in this paper. In addition,according to the property of orthogonal matrix,the explicit expression of minimum norm solution is also derived in the corresponding symmetric and skew-antisymmetric solution set of the matrix equation.

Key concepts: Antisymmetric relation, Skew-symmetric matrix, Mathematics, Matrix (chemical analysis), Symmetric matrix, Square matrix, Mathematical analysis, Singular value decomposition

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