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conjugateGradient: Sparse matrix linear-equation solver

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Sparse matrix linear-equation solver, using the conjugate gradient algorithm. Note that the technique only applies to matrices that are:

  • Symmetric

  • Positive-definite

See http://en.wikipedia.org/wiki/Conjugate_gradient_method for details.

The conjugate gradient method can handle very large sparse matrices, where direct methods (such as LU decomposition) are way too expensive to be useful in practice.

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Versions [RSS] 1.0, 1.1, 1.2, 1.3, 1.4, 2.0, 2.1, 2.2
Dependencies base (>=4 && <5), containers, random [details]
License BSD-3-Clause
Copyright Levent Erkok, 2013
Author Levent Erkok
Maintainer Levent Erkok (erkokl@gmail.com)
Category Math
Home page http://github.com/LeventErkok/ConjugateGradient
Bug tracker http://github.com/LeventErkok/ConjugateGradient/issues
Source repo head: git clone git://github.com/LeventErkok/ConjugateGradient.git
Uploaded by LeventErkok at 2013-04-15T03:53:37Z
Distributions NixOS:2.2
Reverse Dependencies 1 direct, 0 indirect [details]
Downloads 6529 total (28 in the last 30 days)
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Status Docs uploaded by user
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Readme for conjugateGradient-1.1

[back to package description] 
Conjugate Gradient Solver 
=========================

[![Build Status](https://secure.travis-ci.org/LeventErkok/conjugateGradient.png?branch=master)](http://travis-ci.org/LeventErkok/conjugateGradient)

Sparse matrix linear equation solver, using the Conjugate Gradient algorithm: http://en.wikipedia.org/wiki/Conjugate_gradient_method.

The method is applicable to matrices that are symmetric and positive definite.