The fastest way to check if a sparse matrix is singular or not?
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Dear All,
For a large sparse matrix A, how can I check in a fastest way if matrix A is singluar or not? The matrix has a dimension of 6000 x 6000. I know lu is fast, but I need to repeat this calculations many times for different matrix A.
Thanks a lot in advance.
Beson
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Matt J
le 12 Avr 2019
condest(A)
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Matt J
le 13 Avr 2019
Modifié(e) : Matt J
le 13 Avr 2019
The condition number calculated by condest measures how much error magnification you get when you try to invert the matrix when solving a linear equation
The "threshold" that you are pursuing would be determined from the amount of error magnification that your specific application can tolerate (note that it is not possible to have zero error magnification). If the error magnification is greater than what you can tolerate, you would consider the matrix "singular".
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