An inverse eigenvalue problem and an associated approximation problem for generalized K-centrohermitian matrices

A partially described inverse eigenvalue problem and an associated optimal approximation problem for generalized K-centrohermitian matrices are considered. It is shown under which conditions the inverse eigenproblem has a solution. An expression of its general solution is given. In case a solution of the inverse eigenproblem exists, the optimal approximation problem can be solved. The formula of its unique solution is given.     

The generalized eigenvalue problem for certain unsymmetric band matrices

Closed expressions are given for the solution to the generalized eigenproblem for unsymmetric band matrices whose elements repeat in certain ways. An application to the discretization of differential equations is described.     

Methods for the solution ofAXD−BXC=E and its application in the numerical solution of implicit ordinary differential equations

The solution of the equationAXD–BXC=E is discussed, partly in terms of the generalized eigenproblem. Useful applications arise in connection with the numerical solution of implicit differential equations.     

Equilibration of matrices to optimize backward numerical stability

An equilibration is introduced that minimizes the maximum ratio of the upper bounds for the backward rounding error and the inherent error in the given data. This can be applied to the solution of systems of linear equations and to the linear eigenproblem.     

对称广义中心对称矩阵的左右逆特征值问题

研究了对称广义中心对称矩阵的左右逆特征值问题,利用矩阵的奇异值分解(SVD)得到了问题的通解表达式.并由此考虑了解集合对给定矩阵的最佳逼近.     

Numerical Solution of the Consistently Linearized Eigenproblem by Means of a Finite Difference Expression for Approximation of a Directional Derivative in MSC.MARC

More recently, a concept of energy-based categorization of buckling was proposed. It represents a symbiosis of mechanics of solids and spherical geometry. The fundamental mathematical background of this concept is the so-called consistently linearized eigenproblem. The numerical solution of this eigenproblem by means of the finite element method is a key issue of the mentioned concept. This solution is obtained with the help of the commercial finite element software MSC.MARC. An iterative process, involving the programming lanuages PYTHON and FORTRAN 77 and the software MATLAB, is devised, making use of the available element library, of different types of solvers, and of further modeling tools. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An a priori bound for eigenvalue computation by AMLS

Based on Schur complements and modal approximations of submatrices on several levels AMLS constructs a projected eigenproblem which yields good approximations of eigenvalues at the lower end of the spectrum. Rewriting the original problem as a rational eigenproblem of the same dimension as the projected problem, and taking advantage of a minmax characterization for the rational eigenproblem we derive a bound for the AMLS approximation of eigenvalues. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

粘性阻尼线性振动系统的复模态特征值问题的一种新的矩阵摄动分析解法

本文提出了对粘性阻尼线性振动系统的复模态二次广义特征值问题进行高效近似求解的一种新的矩阵摄动分析方法,即先将阻尼矩阵分解为比例阻尼部分和非比例阻尼部分之和,并求得系统的比例阻尼实模态特征解;然后以此为初始值,将阻尼矩阵的非比例部分作为对其比例部分的小量修改,利用摄动分析方法简捷地得到系统的复模态特征值问题的近似解.这一新方法适用于振系阻尼分布不十分偏离比例阻尼情况的问题,因此对大阻尼(非过阻尼)振动系统也有效.这是它优于以前提出的基于无阻尼实模态特征解的类似摄动分析方法的重要特点.文中建立了复模态特征值和特征向量的二阶摄动解式,并通过算例证实了其有效性.此外还讨论了利用比例阻尼假定估计阻尼系统固有振动的复特征值的可行性.     

Two-sided Grassmann–Rayleigh quotient iteration

The two-sided Rayleigh quotient iteration proposed by Ostrowski computes a pair of corresponding left–right eigenvectors of a matrix C. We propose a Grassmannian version of this iteration, i.e., its iterates are pairs of p-dimensional subspaces instead of one-dimensional subspaces in the classical case. The new iteration generically converges locally cubically to the pairs of left–right p-dimensional invariant subspaces of C. Moreover, Grassmannian versions of the Rayleigh quotient iteration are given for the generalized Hermitian eigenproblem, the Hamiltonian eigenproblem and the skew-Hamiltonian eigenproblem.     

Simultaneous iteration for the matrix eigenvalue problem

Let B be a given positive definite Hermitian matrix, and assume the matrix P satisfies the “normality” condition PB^?1P^HB=B^?1P^HBP, where P^H denotes the Hermitian of P. In this paper, we develop an accelerated version of simultaneous iteration for partial solution of the eigenproblem Px=λx. Convergence together with sharp error bounds is obtained. The results are then applied to the solution of the symmetric eigenproblem Ax=λBx, where the algorithms are shown to be improvements over existing techniques.     

A novel modeling method for in-plane eigenproblem estimation of the cable-stayed bridges

A novel modeling method is proposed and used to overcome the in-plane eigenproblem of cable-stayed bridges (CSBs). The modeling method is divided into three steps. Firstly, according to the multi-tower configuration and mechanical characteristics of the CSB, the entire CSB is divided into multiple substructures, namely, a single-tower CSB. Secondly, the substructure is treated by a novel method to make it be a chain-like system and the dynamic triple-beam model with discrete springs is developed. The eigenproblem of the substructure is solved by transfer matrix method (TMM). Then, the entire multi-beam model with discrete springs of the CSB can be obtained by assembling all substructures with consideration of the matching conditions, and the eigenvalue and eigenvector of the CSB can be solved by TMM considering the boundary conditions. The above method is demonstrated by four examples of two kinds of CSBs, namely, semi-floating and rigid-frame CSBs, which are also verified by finite element method (FEM). The proposed model and solution method can be used to calculate the natural frequency and mode shape and evaluate the vertical bending stiffness of the CSB.     

Jacobi-davidson type methods for generalized eigenproblems and polynomial eigenproblems

In this paper we will show how the Jacobi-Davidson iterative method can be used to solve generalized eigenproblems. Similar ideas as for the standard eigenproblem are used, but the projections, that are required to reduce the given problem to a small manageable size, need more attention. We show that by proper choices for the projection operators quadratic convergence can be achieved. The advantage of our approach is that none of the involved operators needs to be inverted. It turns out that similar projections can be used for the iterative approximation of selected eigenvalues and eigenvectors of polynomial eigenvalue equations. This approach has already been used with great success for the solution of quadratic eigenproblems associated with acoustic problems.Our friend Albert died on November 12, 1995     

Multivariate polynomial equations with multiple zeros solved by matrix eigenproblems

Summary. The eigenproblem method calculates the solutions of systems of polynomial equations . It consists in fixing a suitable polynomial and in considering the matrix corresponding to the mapping where the equivalence classes are modulo the ideal generated by The eigenspaces contain vectors, from which all solutions of the system can be read off. This access was investigated in [1] and [16] mainly for the case that is nonderogatory. In the present paper, we study the case where have multiple zeros in common. We establish a kind of Jordan decomposition of reflecting the multiplicity structure, and describe the conditions under which is nonderogatory. The algorithmic analysis of the eigenproblem in the general case is indicated. Received May 20, 1994     

The synthetic hierarchy method: An optimizing approach to obtaining priorities in the AHP

A new method of synthesizing local and criteria priorities into global priorities is suggested. This approach is a development of the Analytic Hierarchy Process enabling the united consideration of all horizontal and vertical connections of a hierarchical system in a single optimizing objective function based on statistical models of the synthesis process. The solution can be reduced to a linear system or to an eigenproblem of a special matrix constructed as a combination of Kronecker's sums and products of pairwise judgement matrices. A numerical example shows that the optimizing approach produces a ranking of global priorities that may be different from the ranking produced by the classical AHP.     

Two-sided harmonic subspace extractions for the generalized eigenvalue problem

One crucial step of the solution of large-scale generalized eigenvalue problems with iterative subspace methods, e.g. Arnoldi, Jacobi-Davidson, is a projection of the original large-scale problem onto a low dimensional subspaces. Here we investigate two-sided methods, where approximate eigenvalues together with their right and left eigenvectors of the full-size problem are extracted from the resulting small eigenproblem. The two-sided Ritz-Galerkin projection can be seen as the most basic form of this approach. It usually provides a good convergence towards the extremal eigenvalues of the spectrum. For improving the convergence towards interior eigenvalues, we investigate two approaches based on harmonic subspace extractions for the generalized eigenvalue problem. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

计算部分奇异值分解的隐式重新启动的双对角化Lanczos方法和精化的双对角化Lanczos方法

The singular value decomposition problem is mathematically equivalent to the eigenproblem of an argumented matrix. Golub et al. give a bidiagonalization Lanczos method for computing a number of largest or smallest singular values and corresponding singular vertors, but the method may encounter some convergence problems. In this paper we analyse the convergence of the method and show why it may fail to converge. To correct this possible nonconvergence, we propose a refined bidiagonalization Lanczos method and apply the implicitly restarting technique to it, and we then present an implicitly restarted bidiagonalization Lanczos algorithm(IRBL) and an implicitly restarted refined bidiagonalization Lanczos algorithm (IRRBL). A new implicitly restarting scheme and a reliable and efficient algorithm for computing refined shifts are developed for this special structure eigenproblem.Theoretical analysis and numerical experiments show that IRRBL performs much better than IRBL.     

多重广义特征值的局部性态

本文给出了含参向量的矩阵多重广义特征值的方向导数，推广了文〔１〕的结果，所得结论对于结构优化和控制系统设计有一定意义。     

G-matrices for algebraically stable general linear methods

This paper describes a technique from Control whereby the G-matrix for an algebraically stable general linear method may be found in terms of the generalised eigenvectors of a generalised eigenproblem associated with the method.     

Backward errors for eigenproblem of two kinds of structured matrices

In this paper, we consider backward errors in the eigenproblem of symmetric centrosymmetric and symmetric skew-centrosymmetric matrices. By making use of the properties of symmetric centrosymmetric and symmetric skew-centrosymmetric matrices, we derive explicit formulae for the backward errors of approximate eigenpairs.     

Calculating Thomson's Spectral Multitapers by Inverse Iteration

Abstract

Spectral estimation using a set of orthogonal tapers is becoming widely used and appreciated in scientific research. It produces direct spectral estimates with more than 2 df at each Fourier frequency, resulting in spectral estimators with reduced variance. Computation of the orthogonal tapers from the basic defining equation is difficult, however, due to the instability of the calculations—the eigenproblem is very poorly conditioned. In this article the severe numerical instability problems are illustrated and then a technique for stable calculation of the tapers—namely, inverse iteration—is described. Each iteration involves the solution of a matrix equation. Because the matrix has Toeplitz form, the Levinson recursions are used to rapidly solve the matrix equation. FORTRAN code for this method is available through the Statlib archive. An alternative stable method is also briefly reviewed.