Sturm theorem for the generalized frank matrix
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One of the popular test matrices for eigenvalue routines is the Frank matrix due to its wellconditioned and poorly conditioned eigenvalues. All the eigenvalues of the Frank matrix are real, positive and different. Sturm Theorem is a very useful tool for computing the eigenvalues of tridiagonal symmetric matrices. In this paper, we apply Sturm Theorem to the generalized Frank matrix which is a special form of the Hessenberg matrix and examine its eigenvalues by using Sturm property. Moreover, we illustrate our results with an example.
SourceHacettepe Journal of Mathematics and Statistics
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