I am looking for a routine that calculate the SVD (singular value decomposition) of a square, complex, dense, non-symmetric matrix. I am aware of Julia's SVD routine (and the respective LAPACK routines that one could call directly). However, I don't need all of the singular values -- I need only the largest one (or some of the largest ones), as well as the associated entries of U. Is there such a routine? I didn't find one in Julia.
I've looked for other packages that could be wrapped, but couldn't find any that offers this feature. The only thing I found is a description of the "svds" Matlab routine, which is apparently based on "eigs". -erik -- Erik Schnetter <[email protected]> http://www.perimeterinstitute.ca/personal/eschnetter/ My email is as private as my paper mail. I therefore support encrypting and signing email messages. Get my PGP key from https://sks-keyservers.net.
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