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Anti-diagonalization theory and algorithm of matrices—from skew-symmetric matrices to arbitrary matrices

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  • Wu, Yunyun
  • Li, Yayun

Abstract

In this paper, a novel algorithm for anti-diagonalization of skew symmetric matrices via using orthogonal similarity transformations has been introduced. The theory and algorithm about the anti-triangular factorization of skew-symmetric matrices are proved. In the case of skew-symmetric matrices, we prove that the anti-diagonal form is always obtained, resulting in developing a new factorization scheme. Moreover, a theoretical algorithm is given based on the theory of double eigenvector system, which provides all the information for the factorization of arbitrary matrices. Finally, the proposed algorithm is verified effective and efficient through the numerical experiments of anti-diagonalization of matrices over a general number field.

Suggested Citation

  • Wu, Yunyun & Li, Yayun, 2023. "Anti-diagonalization theory and algorithm of matrices—from skew-symmetric matrices to arbitrary matrices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 44-54.
    • Handle: RePEc:eee:matcom:v:209:y:2023:i:c:p:44-54
    DOI: 10.1016/j.matcom.2023.01.045
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    References listed on IDEAS

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    1. Singer, Sanja, 2020. "The antitriangular factorization of skew-symmetric matrices," Applied Mathematics and Computation, Elsevier, vol. 381(C).
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