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Computer Solution of Linear Algebraic Systems. By G. Forsythe and C. B. Moler. Pp. xi, 148. 1967. (Prentice-Hall.)

L. Fox
- 01 May 1969 - 
- Vol. 53, Iss: 384, pp 221-222
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This article is published in The Mathematical Gazette.The article was published on 1969-05-01. It has received 489 citations till now.

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Singular value decomposition and least squares solutions

TL;DR: The decomposition of A is called the singular value decomposition (SVD) and the diagonal elements of ∑ are the non-negative square roots of the eigenvalues of A T A; they are called singular values.
Journal ArticleDOI

Hyperquad simulation and speciation (HySS): a utility program for the investigation of equilibria involving soluble and partially soluble species

TL;DR: Hyperquad simulation and speciation (HySS) as mentioned in this paper is a computer program written for the Windows operating system on personal computers which provides simulating titration curves and a system for providing speciation diagrams.
Journal ArticleDOI

What every computer scientist should know about floating-point arithmetic

TL;DR: This paper presents a tutorial on the aspects of floating-point that have a direct impact on designers of computer systems, and concludes with examples of how computer system builders can better support floating point.
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Generalization of backpropagation with application to a recurrent gas market model

TL;DR: This paper will derive a generalization of backpropagation to recurrent systems (which input their own output), such as hybrids of perceptron-style networks and Grossberg/Hopfield networks, and does not require the storage of intermediate iterations to deal with continuous recurrence.
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An algorithm for reducing the bandwidth and profile of a sparse matrix

TL;DR: Extensive testing on finite element matrices indicates that the algorithm typically produces bandwidth and profile which are comparable to those of the commonly-used reverse Cuthill–McKee algorithm, yet requires significantly less computation time.
References
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Dissertation

The AGE iterative methods for solving large linear systems occurring in differential equations

TL;DR: In this article, the authors present an iterative method for solving large linear systems occurring in solving Ordinary and Partial Differential Equations (ODEs and PDEs) using finite difference approximations.
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Generating Test Data with Independently Controllable Features for Multivariate General Linear Forms

TL;DR: An algorithm for constructing test data for any multivariate linear model that provides complete control over the following factors: regression coefficients; regression and residual sums of squares and products matrices; means, standard deviations, and correlations of the independent and dependent variables, residuals, and predicted values.
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Some comments on the solution of linear equations

TL;DR: Computational methods of homogeneous ill-conditioned and singular simultaneous linear equations are discussed in this article, where the authors present a method for computing homogeneous linear equations with singular simultaneous equations.
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