LOBPCG Initial k eigenvectors approximation

2 visualizaciones (últimos 30 días)
frank
frank el 20 de Jul. de 2012
Respondida: Andrew Knyazev el 21 de Sept. de 2018
Hello,
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,
Frank

Respuestas (1)

Andrew Knyazev
Andrew Knyazev el 21 de Sept. de 2018
See https://en.wikipedia.org/wiki/LOBPCG#Convergence_theory_and_practice

Categorías

Más información sobre Eigenvalues & Eigenvectors en Help Center y File Exchange.

Etiquetas

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by