Generation of test matrices with specified eigenvalues using floating-point arithmetic

نویسندگان

چکیده

Abstract This paper concerns test matrices for numerical linear algebra using an error-free transformation of floating-point arithmetic. For specified eigenvalues given by a user, we propose methods generating matrix whose are exactly known based on, example, Schur or Jordan normal form and block diagonal form. It is also possible to produce real with complex eigenvalues. Such useful algorithms in checking the accuracy computed results. In particular, exact errors can be monitored. To generate matrices, first product three Y S X . We approximate ${S^{\prime }}$ S ′ compute ${YS^{\prime }X}$ Y X without rounding error. Next, applied generation Note that constructed may differ from anticipated Finally, examples introduced computations symmetric unsymmetric eigenvalue problems.

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ژورنال

عنوان ژورنال: Numerical Algorithms

سال: 2021

ISSN: ['1017-1398', '1572-9265']

DOI: https://doi.org/10.1007/s11075-021-01186-7