Problem when trying to translate a generalized eigenvalue solution in Matlab into using LAPACK directly
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Hi,
I have recently had a problem related to trying to move a working solution that use the generalized eigenvectors as computed by Matlab into a Java program. I am then trying to call the same routines in LAPACK that I assume Matlab is using (both matrices will be real and symmetric), but then get the eigenvectors scaled by different factors, i.e., if I divide the Matlab eigenvectors with the ones I get from LAPACK when called directly, I get a different scaling for each of the vectors. Regrettably, this makes my solution give a different result - and a wrong one. I would therefore like to know how I should call the LAPACK functions to get the same results as if using Matlab, or any fix that I can use to solve the problem.
As the vectors are not normalized, one is not able to correct this by simply normalizing them.
Thank you for your time.
Regards, Andreas
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