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Journal ArticleDOI

Simplified calculation of eigenvector derivatives

Richard B. Nelson
- 01 Sep 1976 - 
- Vol. 14, Iss: 9, pp 1201-1205
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TLDR
A simplified procedure is presented for the determination of the derivatives of eigenvectors of nth order algebraic eigensystems, applicable to symmetric or nonsymmetric systems, and requires knowledge of only one eigenvalue and its associated right and left eigenavectors.
Abstract
A simplified procedure is presented for the determination of the derivatives of eigenvectors of nth order algebraic eigensystems. The method is applicable to symmetric or nonsymmetric systems, and requires knowledge of only one eigenvalue and its associated right and left eigenvectors. In the procedure, the matrix of the original eigensystem of rank (/?-!) is modified to convert it to a matrix of rank /?, which then is solved directly for a vector which, together with the eigenvector, gives the eigenvector derivative to within an arbitrary constant. The norm of the eigenvector is used to determine this constant and complete the calculation. The method is simple, since the modified n rank matrix is formed without matrix multiplication or extensive manipulation. Since the matrix has the same bandedness as the original eigensystems, it can be treated efficiently using the same banded equation solution algorithms that are used to find the eigenvectors.

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Journal ArticleDOI

An eigenspace method for computing derivatives of semi-simple eigenvalues and corresponding eigenvectors of quadratic eigenvalue problems

TL;DR: This paper proposes a new method for computing derivatives of semi-simple eigenvalues and corresponding eigenvectors of the quadratic matrix polynomial, where the condition number of the coefficient matrix is the ratio of the maximum singular value to the minimum nonzero singular value of Q.

Efficient Computation of Eigenvector Sensitivities for Structural Dynamics via Conjugate Gradients

K. F. Alvin
TL;DR: In this paper, an iterative procedure is presented for computing eigenvector sensitivities due to finite element model parameter variations, which is a Preconditioned Conjugate Projected Gradient-based technique and is intended to utilize the existing matrix factorizations developed for an iteration eigensolution such as Lanczos or Subspace Iteration.
Journal ArticleDOI

New theoretical developments on eigenvector derivatives with repeated eigenvalues

TL;DR: A concept of global design variable is developed in which all intended multivariate design modifications are grouped into a single global variable to which eigenvector derivatives are derived, rendering real major applications of the proposed method to the predictions of structural design modifications.
Journal ArticleDOI

Sensitivity derivatives of eigendata of one-dimensional structural systems

TL;DR: In this paper, a general formulation based on the transfer matrix is presented to calculate the sensitivity derivatives of eigenvalue problems of one-dimensional structural systems, which is equally applicable to any discrete or distributed system of one variable.
Journal ArticleDOI

Second-Order Sensitivity of Smart Structures

TL;DR: A second-order sensitivity analysis for a smart structural system formulated in terms of multiobjective optimization where structural design variables and control parameters are equally treated as design variables is presented in this paper.
References
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Book

The algebraic eigenvalue problem

TL;DR: Theoretical background Perturbation theory Error analysis Solution of linear algebraic equations Hermitian matrices Reduction of a general matrix to condensed form Eigenvalues of matrices of condensed forms The LR and QR algorithms Iterative methods Bibliography.
Journal ArticleDOI

Rates of change of eigenvalues and eigenvectors.

TL;DR: Exact expressions for rates of change of eigenvalues and eigenvector to facilitate computerized design of complex structures are presented.
Journal ArticleDOI

Statistical Identification of Structures

TL;DR: In this paper, a method is formulated for systematically using experimental measurements of the natural frequencies and mode shapes of a structure to modify stiffness and mass characteristics of a finite element model, and an additional feature is that the engineer's confidence in the modeling of the various finite elements is quantified and incorporated into the revision procedure.
Journal ArticleDOI

Handbook for Automatic Computation. Vol II, Linear Algebra

TL;DR: Haida gwaii tourism guide, Handbook of raman spectroscopy, and the Jordan form, Kronecker's form for matrix pencils, and various condition in the Handbook.