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A continuous approximation to the generalized Schur decomposition

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TLDR
In this article, the problem of approximating the generalized Schur decomposition of a matrix pencil A − λ B by a family of differentiable orthogonal transformations is considered and it is shown that when B is nonsingular this approach is feasible and can be expressed as an autonomous differential system.
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This article is published in Linear Algebra and its Applications.The article was published on 1986-06-01 and is currently open access. It has received 12 citations till now. The article focuses on the topics: Schur decomposition & Symmetric matrix.

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Introduction to Numerical Continuation Methods

TL;DR: The Numerical Continuation Methods for Nonlinear Systems of Equations (NCME) as discussed by the authors is an excellent introduction to numerical continuuation methods for solving nonlinear systems of equations.
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Continuation and path following

TL;DR: The main ideas of path following by predictor–corrector and piecewise-linear methods, and their application in the direction of homotopy methods and nonlinear eigenvalue problems are reviewed.
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Linear algebra algorithms as dynamical systems

TL;DR: The notion of dynamical systems as a special realization process for problems arising from the field of linear algebra is exploited to afford unified and fundamental insights into the structure and behaviour of existing discrete methods.
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Nonlinear Poisson Structures and r-Matrices

TL;DR: In this paper, the authors introduce quadratic Poisson structures on Lie groups associated with a class of solutions of the modified Yang-Baxter equation and apply them to the Hamiltonian description of Lax systems.
References
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Matrix computations

Gene H. Golub
Journal ArticleDOI

The Symmetric Eigenvalue Problem.

TL;DR: Parlett as discussed by the authors presents mathematical knowledge that is needed in order to understand the art of computing eigenvalues of real symmetric matrices, either all of them or only a few.
Book

The Symmetric Eigenvalue Problem

TL;DR: Parlett as discussed by the authors presents mathematical knowledge that is needed in order to understand the art of computing eigenvalues of real symmetric matrices, either all of them or only a few.
Book

Linear Algebra