The conjugate gradient method is an algorithm for the numerical solution of systems of linear equations whose matrix is positive semi-definite. It is most often implemented as an iterative algorithm applied to large sparse systems that are too large to solve directly, such as those arising from numerically solving partial differential equations or optimization problems, where it avoids the cost of a direct method like Cholesky decomposition.
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Source Conjugate gradient method (Wikipedia)
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Conjugate gradient method (Wikipedia)
In Field: Computational Science, Lead sentenceQuote, In Field: Computational Science, Lead sentence
conjugate gradient method is an algorithm for the numerical solution of particular systems of linear equations, namely those whose matrix is positive-semidefinite.
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