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An extension of the Cayley transform method for a parameterized generalized inverse eigenvalue problem [PDF]
Numerical Linear Algebra With Applications, 2020 [EN] Since recent studies have shown that the Cayley transform method can be an effective iterative method for solving the inverse eigenvalue problem, in this work, we consider using an extension of it for solving a type of parameterized generalized ...
Masoud Hajarian, Jose E. Roman
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Inverse Problems on the Least Eigenvalue
Results in Mathematics, 2013The paper deals with generalizations of the classical Ambarzumyan theorem, which, as is well-known, can be formulated in the following way: if the first (i.e., smallest) eigenvalue \(\lambda_0\) of the Sturm-Liouville operator \[ Ay:=-y''+q(x)y, \quad ...
Yang, Jie, Yang, Chuan-Fu
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An inverse eigenvalue problem for Hamiltonian matrices
Journal of Computational and Applied Mathematics, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yongxin Yuan, Jinghua Chen
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On the Solution of the Inverse Eigenvalue Complementarity Problem
Journal of Optimization Theory and Applications, 2013The authors consider the inverse eigenvalue linear complementarity problem and propose its global optimization reformulations. They give conditions which provide equivalence between local and global solutions and suggest an enumerative algorithm for finding global solutions of one of formulations. The results of computational experiments are reported.
Carmo P. Brás +2 more
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SIAM Review, 1998
In the inverse eigenvalue problem, one has to construct a matrix with a (partially) given spectrum. The problem appears in many different forms and in many different applications. Usually the problem is constrained in the sense that the matrix \(M\) that one wants to find has to be in a certain class. For example it should be of the form \(M=A+X\) or \(
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In the inverse eigenvalue problem, one has to construct a matrix with a (partially) given spectrum. The problem appears in many different forms and in many different applications. Usually the problem is constrained in the sense that the matrix \(M\) that one wants to find has to be in a certain class. For example it should be of the form \(M=A+X\) or \(
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Solving inverse Pareto eigenvalue problems
Optimization Letters, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Samir Adly, Manh Hung Le
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Journal of Mathematical Physics, 2016
In this article we consider inverse eigenvalue problems for the Schrödinger operator on a finite interval. We extend and strengthen previously known uniqueness theorems. A partially known potential is identified by some sets of eigenvalues and norming constants.
Miklós Horváth, Orsolya Sáfár
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In this article we consider inverse eigenvalue problems for the Schrödinger operator on a finite interval. We extend and strengthen previously known uniqueness theorems. A partially known potential is identified by some sets of eigenvalues and norming constants.
Miklós Horváth, Orsolya Sáfár
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On the Inverse Symmetric Quadratic Eigenvalue Problem
SIAM Journal on Matrix Analysis and Applications, 2014The detailed spectral structure of symmetric, algebraic, quadratic eigenvalue problems has been developed recently. In this paper we take advantage of these canonical forms to provide a detailed analysis of inverse problems of the following form: construct the coefficient matrices from the spectral data including the classical eigenvalue/eigenvector ...
Peter Lancaster, Ion Zaballa
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Inverse Eigenvalue Problems for Complex Matrices
Computing, 1970Wir betrachten die Aufgabe, zu einer komplexen MatrixA eine DiagnonalmatrixV zu finden, so dasA+V (oderVA) vorgeschriebene komplexe Eigenwerte besitzt.
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On some structured inverse eigenvalue problems
Numerical Algorithms, 1997Two special structured inverse eigenvalue problems are investigated. The first one is the Jacobi inverse eigenvalue problem: given some constraints on two sets of reals, find a Jacobi matrix that admits as spectrum and principal subspectrum the two given sets. The polynomial algorithm is based on a special Euclid-Sturm algorithm.
Robert Erra, Bernard Philippe
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