Year: 2007
Journal of Computational Mathematics, Vol. 25 (2007), Iss. 2 : pp. 211–220
Abstract
By applying the generalized singular value decomposition and the canonical correlation decomposition simultaneously, we derive an analytical expression of the optimal approximate solution $\widehat X$, which is both a least-squares symmetric orthogonal anti-symmetric solution of the matrix equation $A^TXA=B$ and a best approximation to a given matrix $X^*$. Moreover, a numerical algorithm for finding this optimal approximate solution is described in detail, and a numerical example is presented to show the validity of our algorithm.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2007-JCM-8686
Journal of Computational Mathematics, Vol. 25 (2007), Iss. 2 : pp. 211–220
Published online: 2007-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10
Keywords: Symmetric orthogonal anti-symmetric matrix Generalized singular value decomposition Canonical correlation decomposition.