# Solving ill posed linear equations

Given a set of linear equations $AX=B$, say $A$ is an ill posed matrix (has a few singular values equal or very close to zero), which numerical algorithm (conjugate gradient, least squares or steepest decent etc ) should be used to obtain the best solution? More specifically, is there a concrete comparison between these methods?

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While your question is on topic here, for future reference you may get better/quicker/more complete answers if you ask it at scicomp.stackexchange.com/questions/tagged/condition-number –  Willie Wong Jan 3 '13 at 14:10
Preconditioning will also be helpful. –  Fixed Point Jan 7 '13 at 22:08