
doi: 10.1007/bf02307382
The authors consider the following problem (called the additive inverse eigenvalue problem): Given \(n + 1\) real symmetric \(n \times n\) matrices \(A_ i\), \(i = 0, 1, \dots, n\), and given \(n\) real numbers \(\lambda_ 1 < \lambda_ 2 < \dots < \lambda_ n\), prove that there are \(n\) real numbers \(c^*_ i\), \(i = 1, \dots, n\), such that the matrix \(A(c) : = A_ 0 + \sum^ n_{i=1} c_ i A_ i\), \(c : = (c_ i) \in \mathbb{R}^ n\), has for \(c_ i = c^*_ i\), \(i = 1,\dots,n\), the prescribed numbers \(\lambda_ i\) as eigenvalues. The authors solve this problem by means of interval computation. The proposed algorithm is based on Newton's method using a new criterion for terminating the iteration, in order to get an approximation \(\widetilde c\) of \(c^* = (c^*_ i)\). The existence of \(c^*\) using one step of the Krawczyk method is verified. Two numerical examples are reported.
Numerical computation of eigenvalues and eigenvectors of matrices, numerical examples, enclosure, prescribed eigenvalue, additive inverse eigenvalue problem, interval computation, Newton's method, Interval and finite arithmetic, Krawczyk method
Numerical computation of eigenvalues and eigenvectors of matrices, numerical examples, enclosure, prescribed eigenvalue, additive inverse eigenvalue problem, interval computation, Newton's method, Interval and finite arithmetic, Krawczyk method
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