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Journal ArticleDOI

Solution of the matrix equation AX + XB = C [F4]

R. H. Bartels, +1 more
- 01 Sep 1972 - 
- Vol. 15, Iss: 9, pp 820-826
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TLDR
The algorithm is supplied as one file of BCD 80 character card images at 556 B.P.I., even parity, on seven ~rack tape, and the user sends a small tape (wt. less than 1 lb.) the algorithm will be copied on it and returned to him at a charge of $10.O0 (U.S.and Canada) or $18.00 (elsewhere).
Abstract
and Canada) or $18.00 (elsewhere). If the user sends a small tape (wt. less than 1 lb.) the algorithm will be copied on it and returned to him at a charge of $10.O0 (U.S. only). All orders are to be prepaid with checks payable to ACM Algorithms. The algorithm is re corded as one file of BCD 80 character card images at 556 B.P.I., even parity, on seven ~rack tape. We will supply the algorithm at a density of 800 B.P.I. if requested. The cards for the algorithm are sequenced starting at 10 and incremented by 10. The sequence number is right justified in colums 80. Although we will make every attempt to insure that the algorithm conforms to the description printed here, we cannot guarantee it, nor can we guarantee that the algorithm is correct.-L.D.F. Descdption The following programs are a collection of Fortran IV sub-routines to solve the matrix equation AX-.}-XB = C (1) where A, B, and C are real matrices of dimensions m X m, n X n, and m X n, respectively. Additional subroutines permit the efficient solution of the equation ArX + xa = C, (2) where C is symmetric. Equation (1) has applications to the direct solution of discrete Poisson equations [2]. It is well known that (1) has a unique solution if and only if the One proof of the result amounts to constructing the solution from complete systems of eigenvalues and eigenvectors of A and B, when they exist. This technique has been proposed as a computational method (e.g. see [1 ]); however, it is unstable when the eigensystem is ill conditioned. The method proposed here is based on the Schur reduction to triangular form by orthogonal similarity transformations. Equation (1) is solved as follows. The matrix A is reduced to lower real Schur form A' by an orthogonal similarity transformation U; that is A is reduced to the real, block lower triangular form.

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Citations
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Journal ArticleDOI

Computing the Positive Stabilizing Solution to Algebraic Riccati Equations With an Indefinite Quadratic Term via a Recursive Method

TL;DR: In this article, an iterative algorithm to solve algebraic Riccati equations with an indefinite quadratic term is proposed, and the global convergence and local quad ratic rate of convergence are guaranteed and a proof is given.
Journal ArticleDOI

Finite iterative solutions to coupled Sylvester-conjugate matrix equations

TL;DR: In this paper, the existence of a solution to a coupled Sylvester-conjugate matrix equation can be determined automatically by using a real inner product in complex matrix spaces as a tool that can be obtained within finite iteration steps for any initial values in the absence of round-off errors.
Journal ArticleDOI

Numerical solution of the lyapunov equation by approximate power iteration

TL;DR: The approximate power iteration (API) algorithm for the computation of the dominant invariant subspace of the solution X of large-order Lyapunov equations AX + XA T + Q = 0 without first computing the matrix X itself is presented.
Proceedings ArticleDOI

An adaptive critic global controller

TL;DR: A nonlinear control system comprising a network of networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design that results in an adaptive controller that is as conservative as the linear designs and as effective as the global controller.
Journal ArticleDOI

The symmetric Procrustes problem

TL;DR: In this article, the singular value decomposition is used to analyse the problem and to derive a stable method for its solution, which is then used to assess the stability of methods based on solving normal equations.
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

The Direct Solution of the Discrete Poisson Equation on a Rectangle

Fred W. Dorr
- 01 Apr 1970 - 
TL;DR: In this article, the authors provide a survey of direct methods for solving finite difference equations with rectilinear domains. But the authors do not discuss whether the methods are easily adaptable to more general regions, and to general elliptic partial differential equations.
Journal ArticleDOI

TheQ R algorithm for real hessenberg matrices

TL;DR: The volume of work involved in a QR step is far less if the matrix is of Hessenberg form, and since there are several stable ways of reducing a general matrix to this form, the QR algorithm is invariably used after such a reduction.
Journal ArticleDOI

Matrix and other direct methods for the solution of systems of linear difference equations

TL;DR: In this paper, the problem of boundary problems arising in the approximate solutions of linear PDEs was investigated. But the work was conducted on desk machines, and the operations involved are, however, capable of being handled efficiently and simply by modern high-speed digital computers.