Esmaeil Kokabifar

Esmaeil Kokabifar, Ghasem Barid Loghmani, S. M. Karbassi

Consider $n \times n$ matrix $A$ and a set $Λ$ consisting of $k \le n$ prescribed complex numbers. Lippert (2010) in a challenging article, studied geometrically the spectral norm distance from $A$ to the set $Λ$ and constructed a perturbation matrix $Δ$ with minimum spectral norm such that $A+Δ$ had $Λ$ in its spectrum. This paper presents an easy practical computational method for constructing the optimal perturbation $Δ$ by extending necessary definitions and lemmas of previous works. Also, some conceivable applications of this issue are provided.

Esmaeil Kokabifar, G. B. Loghmani, A. M. Nazari et al.

Consider an $n \times n$ matrix polynomial $P(λ)$. A spectral norm distance from $P(λ)$ to the set of $n \times n$ matrix polynomials that have a given scalar $μ\in\mathbb{C}$ as a multiple eigenvalue was introduced and obtained by Papathanasiou and Psarrakos. They computed lower and upper bounds for this distance, constructing an associated perturbation of $P(λ)$. In this paper, we extend this result to the case of two given distinct complex numbers $μ_{1}$ and $μ_{2}$. First, we compute a lower bound for the spectral norm distance from $P(λ)$ to the set of matrix polynomials that have $μ_1,μ_2$ as two eigenvalues. Then we construct an associated perturbation of $P(λ)$, such that the perturbed matrix polynomial has two given scalars $μ_1$ and $μ_2$ in its spectrum. Finally, we derive an upper bound for the distance by the constructed perturbation of $P(λ)$. Numerical examples are provided to illustrate the validity of the method.