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documentation update/improvement
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* This decomposition provides the generic approach to solving systems of linear equations, computing
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* the rank, invertibility, inverse, kernel, and determinant.
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*
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* This LU decomposition is very stable and well tested with large matrices. Even exact rank computation
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* works at sizes larger than 1000x1000. However there are use cases where the SVD decomposition is inherently
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* more stable when dealing with numerically damaged input. For example, computing the kernel is more stable with
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* SVD because the SVD can determine which singular values are negligible while LU has to work at the level of matrix
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* coefficients that are less meaningful in this respect.
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*
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* The data of the LU decomposition can be directly accessed through the methods matrixLU(),
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* permutationP(), permutationQ(). Convenience methods matrixL(), matrixU() are also provided.
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* permutationP(), permutationQ().
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*
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* As an exemple, here is how the original matrix can be retrieved:
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* \include class_LU.cpp
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