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| - | == Cholesky Factorization ==
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| - | When the square matrix '''A''' is symmetric and positive definite then it has an efficient triangular decomposition. ''Symmetric'' means that a<sub>ij</sub> = a<sub>ji</sub> for i,j = 1, ... , N. While ''positive definite'' means that <br>
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| - | <math> v \bullet A \bullet v > 0</math> <math> \forall v </math> <br>
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| - | In cholesky factorization we construct a lower triangular matrix '''L''' whose transpose '''L<sup>T</sup>''' can itself serve as upper triangular part. <br>
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| - | In other words we have <br>
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| - | '''L <math>\bullet</math>L<sup>T</sup> = A ''' <br>
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Latest revision as of 09:47, 17 December 2008
