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The generalized singular value decomposition and the general (A-λB)-problem

https://doi.org/10.1007/bf01934915

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Matrix Eigensystem Routines — EISPACK Guide Extension

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Computing theCS decomposition of a partitioned orthonormal matrix

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An approach to solving the spectral problem of A-λB

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Reducing subspaces: Definitions, properties and algorithms

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A method for computing the generalized singular value decomposition

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Perturbation analysis for the generalized eigenvalue and the generalized singular value problem

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The computation of Kronecker's canonical form of a singular pencil

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Kronecker's canonical form and the QZ algorithm

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Linear Differential Equations and Kronecker's Canonical Form

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The Rotation of Eigenvectors by a Perturbation. III

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An Algorithm for Generalized Matrix Eigenvalue Problems

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Towards a Generalized Singular Value Decomposition

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Perturbation Analysis for the Generalized Singular Value Problem

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Error and Perturbation Bounds for Subspaces Associated with Certain Eigenvalue Problems

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Ill-Conditioned Eigensystems and the Computation of the Jordan Canonical Form

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An Algorithm for Numerical Computation of the Jordan Normal Form of a Complex Matrix

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Algorithm 560: JNF, An Algorithm for Numerical Computation of the Jordan Normal Form of a Complex Matrix [F2]

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Methods and algorithms of solving spectral problems for polynomial and rational matrices

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Two Harmonic Jacobi–Davidson Methods for Computing a Partial Generalized Singular Value Decomposition of a Large Matrix Pair

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A Cross-Product Free Jacobi–Davidson Type Method for Computing a Partial Generalized Singular Value Decomposition of a Large Matrix Pair

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On choices of formulations of computing the generalized singular value decomposition of a large matrix pair

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New iterative methods for generalized singular-value problems

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Randomized Algorithms for Computing the Generalized Tensor SVD Based on the Tensor Product

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Computing stable eigendecompositions of matrix pencils

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The dimension of matrices (matrix pencils) with given Jordan (Kronecker) canonical forms

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Eigenvalue computation in the 20th century

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A contour integral-based algorithm for computing generalized singular values

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A Jacobi–Davidson type method for the generalized singular value problem

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A note on simple nonzero finite generalized singular values

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On worst-case condition numbers of a multiple nonzero finite generalized singular value

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Stably Computing the Kronecker Structure and Reducing Subspaces of Singular Pencils A-λ for Uncertain Data

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Eigenvalue computation in the 20th century

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Chapter 6 A survey of matrix computations

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Computational methods for large eigenvalue problems

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Accurate Solutions of Ill-Posed Problems in control theory

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Bounds on Perturbations of Generalized Singular Values and of Associated Subspaces

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RGSVD—AN Algorithm for Computing the Kronecker Structure and Reducing Subspaces of Singular $A - \lambda B$ Pencils

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Computing the Generalized Singular Value Decomposition

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A Higher-Order Generalized Singular Value Decomposition for Rank-Deficient Matrices

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Characterizing GSVD by Singular Value Expansion of Linear Operators and Its Computation

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A Tangent Algorithm for Computing the Generalized Singular Value Decomposition

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The Generalized Eigenvalue Problem for Nonsquare Pencils Using a Minimal Perturbation Approach

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Staircase Failures Explained by Orthogonal Versal Forms

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Condition Number and Backward Error for the Generalized Singular Value Decomposition

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