East Asian J. Appl. Math., 4 (2014), pp. 69-81.
Published online: 2018-02
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Based on various matrix decompositions, we compare different techniques for solving the inverse quadratic eigenvalue problem, where $n×n$ real symmetric matrices $M$, $C$ and $K$ are constructed so that the quadratic pencil $Q(λ) = λ^{2}M+λC+K$ yields good approximations for the given $k$ eigenpairs. We discuss the case where $M$ is positive definite for $1≤ k≤n$, and a general solution to this problem for $n+1≤k≤2n$. The efficiency of our methods is illustrated by some numerical experiments.
}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.100413.021013a}, url = {http://global-sci.org/intro/article_detail/eajam/10822.html} }Based on various matrix decompositions, we compare different techniques for solving the inverse quadratic eigenvalue problem, where $n×n$ real symmetric matrices $M$, $C$ and $K$ are constructed so that the quadratic pencil $Q(λ) = λ^{2}M+λC+K$ yields good approximations for the given $k$ eigenpairs. We discuss the case where $M$ is positive definite for $1≤ k≤n$, and a general solution to this problem for $n+1≤k≤2n$. The efficiency of our methods is illustrated by some numerical experiments.