LOBPCG Initial k eigenvectors approximation

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frank am 20 Jul. 2012
Beantwortet: Andrew Knyazev am 21 Sep. 2018
I am currently working with the lobpcg.py code in python to solve for the eigenvalues and eigenvectors of large sparse matrices. I noticed that the solution is quite sensitive to the initial eigenvectors approximations X.
I am currently using a random function to generate the initial approximations and wanted to know if there is a better about doing this. Could I use a fixed X? Which X could I use to ensure that it will work for many different matrices and still converge?
Thank you,

Antworten (1)

Andrew Knyazev
Andrew Knyazev am 21 Sep. 2018
See https://en.wikipedia.org/wiki/LOBPCG#Convergence_theory_and_practice


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